992 Dataflow Jobs - Page 9

Job Summary We are looking for a seasoned Project Manager with a strong background in Google Cloud Platform (GCP) and DevOps methodologies. The ideal candidate will be responsible for planning, executing, and finalizing projects according to strict deadlines and within budget. This includes acquiring resources and coordinating the efforts of team members and third-party contractors or consultants in order to deliver projects according to plan. The GCP DevOps Project Manager will also define the project’s objectives and oversee quality control throughout its life cycle. Key Responsibilities: ● Lead end-to-end planning, execution, and delivery of Data Foundation initiatives across multiple workstreams (e.g., Data Lake, Observability, IAM, Metadata, Ingestion Pipelines). ● Coordinate across platform, engineering, data governance, cloud infrastructure, and business teams to ensure alignment on scope, dependencies, and delivery timelines. ● Own program-level tracking of deliverables, milestones, risks, and mitigation plans. ● Drive platform enablement efforts (e.g., GCP/AWS setup, Kafka, BigQuery, Snowflake, IAM, monitoring tooling) and ensure their operational readiness. ● Manage stakeholder communications, steering committee updates, and executive reporting. ● Define and manage program OKRs, KPIs, and success metrics. ● Lead technical discussions to assess readiness, unblock execution, and ensure architectural alignment. ● Support cross-team collaboration on data security, access management, observability (Grafana, Prometheus, SIEM), and operational automation. ● Manage vendor relationships and coordinate delivery with third-party partners where applicable. Required Skills and Qualifications ● 8+ years of experience in Technical Program Management or Engineering Program Management roles. ● Proven experience in leading data platform or data foundation programs in a cloud-native environment (GCP, AWS, or Azure). ● Strong knowledge of data platform components : data lakes, ingestion pipelines, metadata tools (e.g., Marquez, Collibra), observability (Grafana, Prometheus), lineage, and data access governance. ● Experience working with DevOps, Security, and Architecture teams to align on infrastructure and platform requirements. ● Familiarity with Agile/Scrum methodologies, Jira/Confluence, and project tracking tools. ● Excellent communication, stakeholder management, and leadership skills. Preferred Qualifications: ● Experience with GCP-native data services (BigQuery, Dataflow, Dataproc, Pub/Sub). ● Working knowledge of IAM models , RBAC/ABAC, and cloud-native security controls. ● Certification in cloud platforms (GCP, AWS, or Azure) or PMP/CSM. ● Exposure to DataOps , CI/CD pipelines , and infrastructure-as-code tools (e.g., Terraform). Thanks & Regards Prashant Awasthi Vastika Technologies PVT LTD 9711189829

Role - Machine Learning Engineer Required Skills & Experience 3+ years of hands-on experience in building, training, and deploying machine learning models in a professional, production-oriented setting. Demonstrable experience with database creation and advanced querying (e.g., SQL, NoSQL), with a strong understanding of data warehousing concepts. Proven expertise in data blending, transformation, and feature engineering , adept at integrating and harmonizing both structured (e.g., relational databases, CSVs) and unstructured (e.g., text, logs, images) data. Strong practical experience with cloud platforms for machine learning development and deployment; significant experience with Google Cloud Platform (GCP) services (e.g., Vertex AI, BigQuery, Dataflow) is highly desirable. Proficiency in programming languages commonly used in data science (e.g., Python is preferred, R). Solid understanding of various machine learning algorithms (e.g., regression, classification, clustering, dimensionality reduction) and experience with advanced techniques like Deep Learning, Natural Language Processing (NLP), or Computer Vision . Experience with machine learning libraries and frameworks (e.g., scikit-learn, TensorFlow, PyTorch ). Familiarity with MLOps tools and practices , including model versioning, monitoring, A/B testing, and continuous integration/continuous deployment (CI/CD) pipelines. Experience with containerization technologies like Docker and orchestration tools like Kubernetes for deploying ML models as REST APIs. Proficiency with version control systems (e.g., Git, GitHub/GitLab) for collaborative development. Interested candidates share cv to dikshith.nalapatla@motivitylabs.com

About us One team. Global challenges. Infinite opportunities. At Viasat, we’re on a mission to deliver connections with the capacity to change the world. For more than 35 years, Viasat has helped shape how consumers, businesses, governments and militaries around the globe communicate. We’re looking for people who think big, act fearlessly, and create an inclusive environment that drives positive impact to join our team. What you'll do The Enterprise Architecture team is focused on providing solutions to enable an effective software engineering workforce that can scale to the business needs. This includes exploring how the business needs map to the application portfolio, business processes, APIs, and data elements across the organization. As a member of this team, you will build up a vast knowledge in software development, cloud application engineering, automation, and container orchestration. Our ideal candidate values communication, learning, adaptability, creativity, and ingenuity. They also enjoy working on challenging technical issues and use creative, innovative techniques to develop and automate solutions. This team is focused on providing our executive and business leadership with visibility into how the software organization is functioning and what opportunities lie to transform the business. In this position you will be an integral part of the Enterprise Architecture team and make meaningful impacts in our journey towards digital transformation. The day-to-day A Strong Data-Model and High-Quality Data are pre-requisites to provide better insights and enable solid data-driven decision making. This is also key to take advantage of various technological advances in Artificial Intelligence and Machine Learning. Your responsibilities will involve build out of data models for various aspects of our enterprise in conjunction with domain experts. Examples include but are not limited to Network, Capacity, Finance, Business Support Systems etc. Responsibilities also include working with software product teams to improve data quality across the organization. What you'll need Bachelor's degree or higher in Computer Science & Applications, Computer Science and Computer & Systems Engineering, Computer Science & Engineering, Computer Science & Mathematics, Computer Science & Network Security and Math & Computer Science, and/or a related field Solid understanding of Data Architecture and Data Engineering principles Experience building out data models Experience performing data analysis and presenting data in easy to comprehend manner. Experience in working with Relational Databases, NoSQL, Large Scale Data technologies (Kafka, Big Query, Snowflake etc) Experience with digital transformation across multiple cloud platforms like AWS and GCP. Experience in modernizing data platforms especially in GCP is highly preferred. Partner with members of Data Platform team and others to build out Data Catalog and map to the data model Detail Oriented to ensure that the catalog represents quality data Solid communication skills and ability to work on a distributed team Tenacity to remain focused on the mission and overcome obstacles Ability to perform hands-on work with development teams and guide them to building necessary data models. Experience setting up governance structure and changing the organization culture by influence What will help you on the job Experience with Cloud Technologies: AWS, GCP, and/or Azure, etc. Expertise in GCP data services like Cloud Pub/Sub, Dataproc, Dataflow, BigQuery, and related technologies preferred. Experience with Airflow, DBT and SQL. Experience with Open-source software like Logstash, ELK stack, Telegraf, Prometheus and OpenTelemetry is a plus. Passionate to deliver solutions that improve developer experience and promote API-first principles and microservices architecture. Experience with Enterprise Architecture and related principles

Key Requirements Technical Skills Expert in GCP services including BigQuery, Dataflow, Pub/Sub, Cloud Composer, Cloud Storage, and Cloud Functions. GCP Professional Data Engineer Certification is highly favourable. Advanced knowledge of SQL for complex data transformation and query optimization. Proven experience in Python for scalable data pipeline development and orchestration following best practices. Experience implementing Terraform for Infrastructure as Code (IaC) to automate GCP resource management. Knowledge of CI/CD pipelines and automated deployment practices. Experience with containerization technologies (e.g., Docker, Kubernetes) Experience building and optimizing batch and streaming data pipelines. Understanding of data governance principles, GCP security (IAM, VPC), and compliance requirements. Soft Skills Demonstrates a growth mindset by actively seeking to learn from peers and stakeholders, fostering a culture of open communication and shared knowledge. Works effectively across teams, including Data Science, Engineering, and Analytics, to understand their needs and deliver impactful data solutions. Actively participates in design discussions, brainstorming sessions, and cross-functional projects, always striving for continuous improvement and innovation. Builds strong relationships across the organization, using empathy and active listening to ensure alignment on goals and deliverables. Approaches challenges with a growth mindset , viewing obstacles as opportunities to innovate and improve processes. Applies a structured and analytical approach to solving complex problems, balancing immediate needs with long-term scalability and efficiency. Demonstrates resilience under pressure, maintaining a positive and solution-focused attitude when faced with tight deadlines or ambiguity. Actively seeks feedback and lessons learned from past projects to continuously refine problem-solving strategies and improve outcomes. Shares expertise generously, guiding team members in adopting best practices and helping them overcome technical challenges. Leads by example, demonstrating how to approach complex problems pragmatically while promoting curiosity and a willingness to explore new tools and technologies. Encourages professional development within the team, supporting individuals in achieving their career goals and obtaining certifications, especially within the Google Cloud ecosystem. Main duties and responsibilities Design, develop, and maintain scalable data pipelines using modern data engineering tools and technologies on our GCP stack. Build and optimize our lake house on Google Cloud Platform (GCP) Implement data ingestion, transformation, and loading processes for various data sources (e.g., databases, APIs, cloud storage) Ensure data quality, consistency, and security throughout the data pipeline Leverage GCP services (e.g., Dataflow, Dataproc, BigQuery, Cloud Storage) to build and maintain cloud-native data solutions Implement infrastructure as code (IaC) principles using Terraform to automate provisioning and configuration Manage and optimize cloud resources to ensure cost-efficiency and performance Design and implement efficient data models following a star schema approach to support analytical and operational workloads Collaborate with data analysts to develop advanced analytics solutions. Conduct data quality analysis to drive better data management on outputs in our Curated Layer. Mentor junior data engineers and provide technical guidance Contribute to the development of data engineering best practices and standards Collaborate with cross-functional teams to deliver complex data projects

What you’ll do? Design, develop, and operate high scale applications across the full engineering stack. Design, develop, test, deploy, maintain, and improve software. Apply modern software development practices (serverless computing, microservices architecture, CI/CD, infrastructure-as-code, etc.) Work across teams to integrate our systems with existing internal systems, Data Fabric, CSA Toolset. Participate in technology roadmap and architecture discussions to turn business requirements and vision into reality. Participate in a tight-knit, globally distributed engineering team. Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on network, or service operations and quality. Research, create, and develop software applications to extend and improve on Equifax Solutions. Manage sole project priorities, deadlines, and deliverables. Collaborate on scalability issues involving access to data and information. Actively participate in Sprint planning, Sprint Retrospectives, and other team activity What Experience You Need Bachelor's degree or equivalent experience 5+ years of relevant software engineering experience 5+ years experience writing, debugging, and troubleshooting code in mainstream Java, SpringBoot, TypeScript/JavaScript, HTML, CSS 5+ years experience with Cloud technology: GCP, AWS, or Azure 5+ years experience designing and developing cloud-native solutions 5+ years experience designing and developing microservices using Java, SpringBoot, GCP SDKs, GKE/Kubernetes 5+ years experience deploying and releasing software using Jenkins CI/CD pipelines, understand infrastructure-as-code concepts, Helm Charts, and Terraform constructs What could set you apart Self-starter that identifies/responds to priority shifts with minimal supervision. Experience designing and developing big data processing solutions using Dataflow/Apache Beam, Bigtable, BigQuery, PubSub, GCS, Composer/Airflow, and others UI development (e.g. HTML, JavaScript, Angular and Bootstrap) Experience with backend technologies such as JAVA/J2EE, SpringBoot, SOA and Microservices Source code control management systems (e.g. SVN/Git, Github) and build tools like Maven & Gradle. Agile environments (e.g. Scrum, XP) Relational databases (e.g. SQL Server, MySQL) Atlassian tooling (e.g. JIRA, Confluence, and Github) Developing with modern JDK (v1.7+) Automated Testing: JUnit, Selenium, LoadRunner, SoapUI Cloud Certification strongly preferred

```html About the Company Strong Experience in Big Data- Data Modelling, Design, Architecting & Solutioning. About the Role Understands programming language like SQL, Python, R-Scala. Responsibilities Good Python skills. Experience from data visualisation tools such as Google Data Studio or Power BI. Knowledge in A/B Testing, Statistics, Google Cloud Platform, Google Big Query, Agile Development, DevOps, Date Engineering, ETL Data Processing. Strong Migration experience of production Hadoop Cluster to Google Cloud. Qualifications Good To Have:- Required Skills Expert in Big Query, Dataproc, Data Fusion, Dataflow, Bigtable, Fire Store, CloudSQL, Cloud Spanner, Google Cloud Storage, Cloud Composer, Cloud Interconnect, Etc. Preferred Skills None specified. Pay range and compensation package Not specified. Equal Opportunity Statement Not specified. ```

Equifax is where you can power your possible. If you want to achieve your true potential, chart new paths, develop new skills, collaborate with bright minds, and make a meaningful impact, we want to hear from you. What you’ll do? Design, develop, and operate high scale applications across the full engineering stack. Design, develop, test, deploy, maintain, and improve software. Apply modern software development practices (serverless computing, microservices architecture, CI/CD, infrastructure-as-code, etc.) Work across teams to integrate our systems with existing internal systems, Data Fabric, CSA Toolset. Participate in technology roadmap and architecture discussions to turn business requirements and vision into reality. Participate in a tight-knit, globally distributed engineering team. Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on network, or service operations and quality. Research, create, and develop software applications to extend and improve on Equifax Solutions. Manage sole project priorities, deadlines, and deliverables. Collaborate on scalability issues involving access to data and information. Actively participate in Sprint planning, Sprint Retrospectives, and other team activity What Experience You Need Bachelor's degree or equivalent experience 5+ years of relevant software engineering experience 5+ years experience writing, debugging, and troubleshooting code in mainstream Java, SpringBoot, TypeScript/JavaScript, HTML, CSS 5+ years experience with Cloud technology: GCP, AWS, or Azure 5+ years experience designing and developing cloud-native solutions 5+ years experience designing and developing microservices using Java, SpringBoot, GCP SDKs, GKE/Kubernetes 5+ years experience deploying and releasing software using Jenkins CI/CD pipelines, understand infrastructure-as-code concepts, Helm Charts, and Terraform constructs What could set you apart Self-starter that identifies/responds to priority shifts with minimal supervision. Experience designing and developing big data processing solutions using Dataflow/Apache Beam, Bigtable, BigQuery, PubSub, GCS, Composer/Airflow, and others UI development (e.g. HTML, JavaScript, Angular and Bootstrap) Experience with backend technologies such as JAVA/J2EE, SpringBoot, SOA and Microservices Source code control management systems (e.g. SVN/Git, Github) and build tools like Maven & Gradle. Agile environments (e.g. Scrum, XP) Relational databases (e.g. SQL Server, MySQL) Atlassian tooling (e.g. JIRA, Confluence, and Github) Developing with modern JDK (v1.7+) Automated Testing: JUnit, Selenium, LoadRunner, SoapUI Cloud Certification strongly preferred We offer a hybrid work setting, comprehensive compensation and healthcare packages, attractive paid time off, and organizational growth potential through our online learning platform with guided career tracks. Are you ready to power your possible? Apply today, and get started on a path toward an exciting new career at Equifax, where you can make a difference! Who is Equifax? At Equifax, we believe knowledge drives progress. As a global data, analytics and technology company, we play an essential role in the global economy by helping employers, employees, financial institutions and government agencies make critical decisions with greater confidence. We work to help create seamless and positive experiences during life’s pivotal moments: applying for jobs or a mortgage, financing an education or buying a car. Our impact is real and to accomplish our goals we focus on nurturing our people for career advancement and their learning and development, supporting our next generation of leaders, maintaining an inclusive and diverse work environment, and regularly engaging and recognizing our employees. Regardless of location or role, the individual and collective work of our employees makes a difference and we are looking for talented team players to join us as we help people live their financial best. Equifax is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

Data Scientist – Recommender Systems Location: Bengaluru (Hybrid) Role Summary We’re seeking a skilled Data Scientist with deep expertise in recommender systems to design and deploy scalable personalization solutions. This role blends research, experimentation, and production-level implementation, with a focus on content-based and multi-modal recommendations using deep learning and cloud-native tools. Responsibilities Research, prototype, and implement recommendation models: two-tower, multi-tower, cross-encoder architectures Utilize text/image embeddings (CLIP, ViT, BERT) for content-based retrieval and matching Conduct semantic similarity analysis and deploy vector-based retrieval systems (FAISS, Qdrant, ScaNN) Perform large-scale data prep and feature engineering with Spark/PySpark and Dataproc Build ML pipelines using Vertex AI, Kubeflow, and orchestration on GKE Evaluate models using recommender metrics (nDCG, Recall@K, HitRate, MAP) and offline frameworks Drive model performance through A/B testing and real-time serving via Cloud Run or Vertex AI Address cold-start challenges with metadata and multi-modal input Collaborate with engineering for CI/CD, monitoring, and embedding lifecycle management Stay current with trends in LLM-powered ranking, hybrid retrieval, and personalization Required Skills Python proficiency with pandas, polars, numpy, scikit-learn, TensorFlow, PyTorch, transformers Hands-on experience with deep learning frameworks for recommender systems Solid grounding in embedding retrieval strategies and approximate nearest neighbor search GCP-native workflows: Vertex AI, Dataproc, Dataflow, Pub/Sub, Cloud Functions, Cloud Run Strong foundation in semantic search, user modeling, and personalization techniques Familiarity with MLOps best practices—CI/CD, infrastructure automation, monitoring Experience deploying models in production using containerized environments and Kubernetes Nice to Have Ranking models knowledge: DLRM, XGBoost, LightGBM Multi-modal retrieval experience (text + image + tabular features) Exposure to LLM-powered personalization or hybrid recommendation systems Understanding of real-time model updates and streaming ingestion

UST is looking for a talented GCP Data Engineer with 6 to 10 years of experience to join our team and play a crucial role in designing and implementing efficient data solutions on the Google Cloud Platform (GCP). The ideal candidate should possess strong data engineering skills, expertise in GCP services, and proficiency in data processing technologies, particularly PySpark. Responsibilitie s:Data Pipeline Developmen t:Design, implement, and optimize end-to-end data pipelines on GCP, focusing on scalability and performanc e.Develop and maintain ETL workflows for seamless data processin g.GCP Cloud Expertis e:Utilize GCP services such as BigQuery, Cloud Storage, and Dataflow for effective data engineerin g.Implement and manage data storage solutions on GC P.Data Transformation with PySpar k:Leverage PySpark for advanced data transformations, ensuring high-quality and well-structured outpu t.Implement data cleansing, enrichment, and validation processes using PySpar k. Requirem ents:Proven experience as a Data Engineer, with a strong emphasis on GCP.Proficiency in GCP services such as BigQuery, Cloud Storage, and Data flow.Expertise in PySpark for data processing and analytics is a must.Experience with data modeling, ETL processes, and data warehou sing.Proficiency in programming languages such as Python, SQL, or Scala for data proces sing.Relevant certifications in GCP or data engineering are plus. Skills GCP, PySpark

Location: Hyderabad Employment Type: Full Time Join our team as a SAP HANA 2.0 Architect and lead the design and implementation of cutting-edge data integration solutions on Google Cloud Platform (GCP). If you’re passionate about SAP, cloud data architectures, and enabling analytics at scale, we want to connect with you! What You’ll Do Architect and manage SAP HANA 2.0 and SAP ECC deployments on GCP. Design scalable data extraction frameworks (master, transactional, CDC) from SAP ERP modules (FI, CO, SD, MM, PP, HR, etc.) to data lakes. Develop robust ETL/ELT pipelines, ensuring data quality and governance. Evaluate and implement SAP-native and third-party data extraction tools (ODP, SLT, SAP Data Services, ABAP frameworks). Collaborate with infrastructure and business teams to deliver secure, high-performance, and cost-effective solutions. Produce architecture diagrams and technical documentation. Mentor and lead SAP technical consultants and data engineers. Troubleshoot integration and performance issues, driving optimization. Stay current on trends in SAP HANA, GCP, and data integration. What We’re Looking For 10+ years SAP ERP experience, with 5+ years in SAP HANA 2.0. Proven deployment and management of SAP HANA on GCP. Hands-on SAP ECC (v6.0+) experience across multiple modules. Deep knowledge of SAP data models, tables, and integration. Expertise in data extraction: OData, BW Extractors, RFC, BAPI, CDS Views, SLT, ABAP, and integration with data lakes. Experience with cloud-native ETL/ELT tools (Google Dataflow, Apache Beam, Informatica, etc.). Strong SAP HANA modeling, SQL scripting, and performance tuning skills. Familiarity with GCP services: BigQuery, Cloud Storage, Dataflow, Pub/Sub, Composer/Airflow. Understanding of security best practices for SAP data in the cloud. Excellent communication, leadership, and mentoring skills. Preferred Qualifications Bachelor’s or Master’s in Computer Science, IT, or related field. SAP Certified Technology Associate — SAP HANA 2.0. GCP Certified Architect or equivalent. Ready to architect the future of data-driven SAP solutions? Apply now and be part of a dynamic team driving innovation in enterprise data integration! #SAPJobs #HANAAchitect #GCP #DataLake #ETL #CloudJobs #HyderabadJobs #SAPCareers #NowHiring

Syensqo is all about chemistry. We’re not just referring to chemical reactions here, but also to the magic that occurs when the brightest minds get to work together. This is where our true strength lies. In you. In your future colleagues and in all your differences. And of course, in your ideas to improve lives while preserving our planet’s beauty for the generations to come. Join us at Syensqo, where our IT team is gearing up to enhance its capabilities. We play a crucial role in the group's transformation—accelerating growth, reshaping progress, and creating sustainable shared value. IT team is making operational adjustments to supercharge value across the entire organization. Here at Syensqo, we're one strong team! Our commitment to accountability drives us as we work hard to deliver value for our customers and stakeholders. In our dynamic and collaborative work environment, we add a touch of enjoyment while staying true to our motto: reinvent progress. Come be part of our transformation journey and contribute to the change as a future team member. We are looking for: As a Data/ML Engineer, you will play a central role in defining, implementing, and maintaining cloud governance frameworks across the organization. You will collaborate with cross-functional teams to ensure secure, compliant, and efficient use of cloud resources for data and machine learning workloads. Your expertise in full-stack automation, DevOps practices, and Infrastructure as Code (IaC) will drive the standardization and scalability of our cloud-based data and ML platforms. Key requirements are: Ensuring cloud data governance Define and maintain central cloud governance policies, standards, and best practices for data, AI and ML workloads Ensure compliance with security, privacy, and regulatory requirements across all cloud environments Monitor and optimize cloud resource usage, cost, and performance for data, AI and ML workloads Design and Implement Data Pipelines Co-develop, co-construct, test, and maintain highly scalable and reliable data architectures, including ETL processes, data warehouses, and data lakes with the Data Platform Team Build and Deploy ML Systems Co-design, co-develop, and deploy machine learning models and associated services into production environments, ensuring performance, reliability, and scalability Infrastructure Management Manage and optimize cloud-based infrastructure (e.g., AWS, Azure, GCP) for data storage, processing, and ML model serving Collaboration Work collaboratively with data scientists, ML engineers, security and business stakeholders to align cloud governance with organizational needs Provide guidance and support to teams on cloud architecture, data management, and ML operations. Work collaboratively with other teams to transition prototypes and experimental models into robust, production-ready solutions Data Governance and Quality: Implement best practices for data governance, data quality, and data security to ensure the integrity and reliability of our data assets. Performance and Optimisation: Identify and implement performance improvements for data pipelines and ML models, optimizing for speed, cost-efficiency, and resource utilization. Monitoring and Alerting Establish and maintain monitoring, logging, and alerting systems for data pipelines and ML models to proactively identify and resolve issues Tooling and Automation Design and implement full-stack automation for data pipelines, ML workflows, and cloud infrastructure Build and manage cloud infrastructure using IaC tools (e.g., Terraform, CloudFormation) Develop and maintain CI/CD pipelines for data and ML projects Promote DevOps culture and best practices within the organization Develop and maintain tools and automation scripts to streamline data operations, model training, and deployment processes Stay Current on new ML / AI trends: Keep abreast of the latest advancements in data engineering, machine learning, and cloud technologies, evaluating and recommending new tools and approach Document processes, architectures, and standards for knowledge sharing and onboarding Education and experience Education: Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related quantitative field. (Relevant work experience may be considered in lieu of a degree). Programming: Strong proficiency in Python (essential) and experience with other relevant languages like Java, Scala, or Go. Data Warehousing/Databases: Solid understanding and experience with relational databases (e.g., PostgreSQL, MySQL) and NoSQL databases (e.g., MongoDB, Cassandra). Experience with data warehousing solutions (e.g., Snowflake, Redshift, BigQuery) is highly desirable. Big Data Technologies: Hands-on experience with big data processing frameworks (e.g., Spark, Flink, Hadoop). Cloud Platforms: Experience with at least one major cloud provider (AWS, Azure, or GCP) and their relevant data and ML services (e.g., S3, EC2, Lambda, EMR, SageMaker, Dataflow, BigQuery, Azure Data Factory, Azure ML). ML Concepts: Fundamental understanding of machine learning concepts, algorithms, and workflows. MLOps Principles: Familiarity with MLOps principles and practices for deploying, monitoring, and managing ML models in production. Version Control: Proficiency with Git and collaborative development workflows. Problem-Solving: Excellent analytical and problem-solving skills with a strong attention to detail. Communication: Strong communication skills, able to articulate complex technical concepts to both technical and non-technical stakeholders. Bonus Points (Highly Desirable Skills & Experience): Experience with containerisation technologies (Docker, Kubernetes). Familiarity with CI/CD pipelines for data and ML deployments. Experience with stream processing technologies (e.g., Kafka, Kinesis). Knowledge of data visualization tools (e.g., Tableau, Power BI, Looker). Contributions to open-source projects or a strong portfolio of personal projects. Experience with [specific domain knowledge relevant to your company, e.g., financial data, healthcare data, e-commerce data]. Language skills Fluent English What’s in it for the candidate Be part of a highly motivated team of explorers Help make a difference and thrive in Cloud and AI technology Chart your own course and build a fantastic career Have fun and enjoy life with an industry leading remuneration pack About us Syensqo is a science company developing groundbreaking solutions that enhance the way we live, work, travel and play. Inspired by the scientific councils which Ernest Solvay initiated in 1911, we bring great minds together to push the limits of science and innovation for the benefit of our customers, with a diverse, global team of more than 13,000 associates. Our solutions contribute to safer, cleaner, and more sustainable products found in homes, food and consumer goods, planes, cars, batteries, smart devices and health care applications. Our innovation power enables us to deliver on the ambition of a circular economy and explore breakthrough technologies that advance humanity. At Syensqo, we seek to promote unity and not uniformity. We value the diversity that individuals bring and we invite you to consider a future with us, regardless of background, age, gender, national origin, ethnicity, religion, sexual orientation, ability or identity. We encourage individuals who may require any assistance or accommodations to let us know to ensure a seamless application experience. We are here to support you throughout the application journey and want to ensure all candidates are treated equally. If you are unsure whether you meet all the criteria or qualifications listed in the job description, we still encourage you to apply.

Role description Exp 5 8 yr Location Hyd JD Pyspark developer to work on a range of datadriven projects using PysparkSQLPython and Apache Airflow for Job scheduling and orchestration on Google Cloud PlatformGCPIn this this role you will be responsible for implementing data pipelines processing large datasets writing sql queries and ensuring smooth orchestration and automation of jobs using Airflow Required Skills Qualifications Experience with Pyspark for data processing and largescale data processing Proficiency in SQL for writing complex queries and optimizing database operations Strong knowledge of Python and experience in using Python libraries like Pandas and Numpy Handsonexperience with Apache Airflow for job scheduling DAG creation and workflow management experience working with Google Cloud PlatformGCP including Goolg Cloud StorageGCS BigQuery Dataflow and Dataproc Strong understanding of ETL processes and data pipeline development Familiarity with version control systems like Git Skills Mandatory Skills : GCP Storage,GCP BigQuery,GCP DataProc,GCP Cloud Composer,GCP DMS,Apache airflow,Java,Python,Scala,GCP Datastream,Google Analytics Hub,GCP Workflows,GCP Dataform,GCP Datafusion,GCP Pub/Sub,ANSI-SQL,GCP Dataflow,GCP Data Flow,GCP Cloud Pub/Sub,Big Data Hadoop Ecosystem

When you join Verizon You want more out of a career. A place to share your ideas freely even if theyre daring or different. Where the true you can learn, grow, and thrive. At Verizon, we power and empower how people live, work, and play by connecting them to what brings them joy. We do what we love driving innovation, creativity, and impact in the world. Our V Team is a community of people who anticipate, lead, and believe that listening is where learning begins. In crisis and in celebration, we come together lifting our communities and building trust in how we show up, everywhere & always. Want in? Join the #VTeamLife. What Youll Be Doing... As an Engineer II - Data Engineering in the Artificial Intelligence and Data Organization (AI&D) , you will drive various activities including data engineering, data operations automation, data frameworks, and platforms to improve the efficiency, customer experience, and profitability of the company. At Verizon, we are on a journey to industrialize our data science and AI capabilities. Very simply, this means that AI will fuel all decisions and business processes across the company. With our leadership in bringing the 5G network nationwide, the opportunity for AI will only grow exponentially in going from enabling billions of predictions to possibly trillions of predictions that are automated and real-time. Building high-quality Data Engineering applications. Design and implement data pipelines using Apache Airflow via Composer, Dataflow, and Dataproc for batch and streaming workloads. Develop and optimize SQL queries and data models in BigQuery to support downstream analytics and reporting. Automate data ingestion, transformation, and export processes across various GCP components using Cloud Functions and Cloud Run. Monitor and troubleshoot data workflows using Cloud Monitoring and Cloud Logging to ensure system reliability and performance. Collaborate with data analysts, scientists, and business stakeholders to gather requirements and deliver data-driven solutions. Ensure adherence to data security, quality, and governance best practices throughout the pipeline lifecycle. Support the deployment of production-ready data solutions and assist in performance tuning and scalability efforts. Debugging the production failures and identifying the solution. Working on ETL/ELT development. What were looking for... We are looking for a highly motivated and skilled Engineer II Data Engineer with strong experience in Google Cloud Platform (GCP) to join our growing data engineering team. The ideal candidate will work on building and maintaining scalable data pipelines and cloud-native workflows using a wide range of GCP services such as Airflow (Composer), BigQuery, Dataflow, Dataproc, Cloud Functions, Cloud Run, Cloud Monitoring, and Cloud Logging. You'll Need To Have Bachelor's or one or more years of work experience. Two or more years of relevant work experience. Two or more years of relevant work experience in GCP. Hands-on experience with Google Cloud Platform (GCP) and services such as: Airflow (Composer) for workflow orchestration BigQuery for data warehousing and analytics Dataflow for scalable data processing Dataproc for Spark/Hadoop-based jobs Cloud Functions and Cloud Run for event-driven and container-based computing Cloud Monitoring and Logging for observability and alerting Proficiency in Python for scripting and pipeline development. Good understanding of SQL, data modelling, and data transformation best practices. Ability to troubleshoot complex data issues and optimize performance. Ability to effectively communicate through presentation, interpersonal, verbal, and written skills. Strong communication skills, collaboration, problem-solving, analytical, and critical-thinking skills. Even better if you have one or more of the following: Master's degree in Computer Science, Information Systems, and/or related technical discipline. Hands-on experience with AI/ML Models and Agentic AI building, tuning, and deploying for Data Engineering applications. Big Data Analytics Certification in Google Cloud. Hands-on experience with Hadoop-based environments (HDFS, Hive, Spark, Dataproc). Knowledge of cost optimization techniques for cloud workloads. Knowledge of telecom architecture. If Verizon and this role sound like a fit for you, we encourage you to apply even if you dont meet every even better qualification listed above. Where youll be working In this hybrid role, you'll have a defined work location that includes work from home and assigned office days set by your manager. Scheduled Weekly Hours 40 Equal Employment Opportunity Verizon is an equal opportunity employer. We evaluate qualified applicants without regard to race, gender, disability, or any other legally protected characteristics. Locations Hyderabad, India Bangalore, India Chennai, India

Data Engineering - GCP-Bigquery Pune, India Job description Mandatory skills ANSISQL Apache airflow GCP BigQuery GCP Cloud Composer GCP Dataflow GCP Dataform GCP Datafusion GCP DataProc GCP Datastream GCP DMS GCP PubSub GCP Storage GCP Workflows Google Analytics Hub Java Python Scala 5 years Experience in GCP BigQuery Oracle PLSQL Good knowledge of GCP tools such as GCS DataFlow Cloud Composer Cloud Pub Sub Proficient in Big Query DBMS and BQL Able to design end to end batch process in GCP Competent in Linux and python scripting Terraform Scripting for creating the GCP infrastructure Good communication skills Proficient with CICD tools like GitHub Jenkins Nexus

Industry & Sector Operating at the crossroads of financial services and advanced analytics, our client delivers cloud-native data platforms that unlock enterprise-scale insights and regulatory reporting. The organization champions Google Cloud innovation to modernize legacy warehouses and fuel AI-driven products. Role & Responsibilities Design, build and optimize petabyte-scale data marts on BigQuery for analytics and ML workloads. Develop ELT pipelines with Dataflow, Apache Beam and Cloud Composer, ensuring end-to-end observability. Implement partitioning, clustering and columnar compression strategies to reduce query cost and latency. Orchestrate batch and streaming workflows integrating Pub/Sub, Cloud Storage and external databases. Enforce data governance, lineage and security via IAM, DLP and encryption best practices. Partner with product, BI and ML teams to translate business questions into performant SQL and repeatable templates. Skills & Qualifications Must-Have 4+ years data engineering on GCP. Expert SQL and schema design in BigQuery. Proficient Python or Java with Beam SDK. Hands-on building Composer/Airflow DAGs. ETL performance tuning and cost optimization. Git, CI/CD and Terraform proficiency. Preferred Experience with Looker or Data Studio. Familiarity with Kafka or Pub/Sub streaming patterns. Data Quality tooling like Great Expectations. Spark on Dataproc or Vertex AI exposure. Professional Data Engineer certification. BFSI analytics domain knowledge. Benefits & Culture Highlights Modern Bengaluru campus with on-site labs and wellness facilities. Annual GCP certification sponsorship and dedicated learning budget. Performance-linked bonus and accelerated career paths. Skills: vertex ai,data studio,airflow,terraform,ci/cd,spark,beam sdk,bigquery,etl performance tuning,kafka,git,dataproc,data quality tooling,gcp,sql,schema design,java,cost optimization,etl,python,composer,looker,pub/sub

Industry & Sector Operating at the crossroads of financial services and advanced analytics, our client delivers cloud-native data platforms that unlock enterprise-scale insights and regulatory reporting. The organization champions Google Cloud innovation to modernize legacy warehouses and fuel AI-driven products. Role & Responsibilities Design, build and optimize petabyte-scale data marts on BigQuery for analytics and ML workloads. Develop ELT pipelines with Dataflow, Apache Beam and Cloud Composer, ensuring end-to-end observability. Implement partitioning, clustering and columnar compression strategies to reduce query cost and latency. Orchestrate batch and streaming workflows integrating Pub/Sub, Cloud Storage and external databases. Enforce data governance, lineage and security via IAM, DLP and encryption best practices. Partner with product, BI and ML teams to translate business questions into performant SQL and repeatable templates. Skills & Qualifications Must-Have 4+ years data engineering on GCP. Expert SQL and schema design in BigQuery. Proficient Python or Java with Beam SDK. Hands-on building Composer/Airflow DAGs. ETL performance tuning and cost optimization. Git, CI/CD and Terraform proficiency. Preferred Experience with Looker or Data Studio. Familiarity with Kafka or Pub/Sub streaming patterns. Data Quality tooling like Great Expectations. Spark on Dataproc or Vertex AI exposure. Professional Data Engineer certification. BFSI analytics domain knowledge. Benefits & Culture Highlights Modern Bengaluru campus with on-site labs and wellness facilities. Annual GCP certification sponsorship and dedicated learning budget. Performance-linked bonus and accelerated career paths. Skills: vertex ai,data studio,airflow,terraform,ci/cd,spark,beam sdk,bigquery,etl performance tuning,kafka,git,dataproc,data quality tooling,gcp,sql,schema design,java,cost optimization,etl,python,composer,looker,pub/sub

Industry & Sector Operating at the crossroads of financial services and advanced analytics, our client delivers cloud-native data platforms that unlock enterprise-scale insights and regulatory reporting. The organization champions Google Cloud innovation to modernize legacy warehouses and fuel AI-driven products. Role & Responsibilities Design, build and optimize petabyte-scale data marts on BigQuery for analytics and ML workloads. Develop ELT pipelines with Dataflow, Apache Beam and Cloud Composer, ensuring end-to-end observability. Implement partitioning, clustering and columnar compression strategies to reduce query cost and latency. Orchestrate batch and streaming workflows integrating Pub/Sub, Cloud Storage and external databases. Enforce data governance, lineage and security via IAM, DLP and encryption best practices. Partner with product, BI and ML teams to translate business questions into performant SQL and repeatable templates. Skills & Qualifications Must-Have 4+ years data engineering on GCP. Expert SQL and schema design in BigQuery. Proficient Python or Java with Beam SDK. Hands-on building Composer/Airflow DAGs. ETL performance tuning and cost optimization. Git, CI/CD and Terraform proficiency. Preferred Experience with Looker or Data Studio. Familiarity with Kafka or Pub/Sub streaming patterns. Data Quality tooling like Great Expectations. Spark on Dataproc or Vertex AI exposure. Professional Data Engineer certification. BFSI analytics domain knowledge. Benefits & Culture Highlights Modern Bengaluru campus with on-site labs and wellness facilities. Annual GCP certification sponsorship and dedicated learning budget. Performance-linked bonus and accelerated career paths. Skills: vertex ai,data studio,airflow,terraform,ci/cd,spark,beam sdk,bigquery,etl performance tuning,kafka,git,dataproc,data quality tooling,gcp,sql,schema design,java,cost optimization,etl,python,composer,looker,pub/sub

Industry & Sector Operating at the crossroads of financial services and advanced analytics, our client delivers cloud-native data platforms that unlock enterprise-scale insights and regulatory reporting. The organization champions Google Cloud innovation to modernize legacy warehouses and fuel AI-driven products. Role & Responsibilities Design, build and optimize petabyte-scale data marts on BigQuery for analytics and ML workloads. Develop ELT pipelines with Dataflow, Apache Beam and Cloud Composer, ensuring end-to-end observability. Implement partitioning, clustering and columnar compression strategies to reduce query cost and latency. Orchestrate batch and streaming workflows integrating Pub/Sub, Cloud Storage and external databases. Enforce data governance, lineage and security via IAM, DLP and encryption best practices. Partner with product, BI and ML teams to translate business questions into performant SQL and repeatable templates. Skills & Qualifications Must-Have 4+ years data engineering on GCP. Expert SQL and schema design in BigQuery. Proficient Python or Java with Beam SDK. Hands-on building Composer/Airflow DAGs. ETL performance tuning and cost optimization. Git, CI/CD and Terraform proficiency. Preferred Experience with Looker or Data Studio. Familiarity with Kafka or Pub/Sub streaming patterns. Data Quality tooling like Great Expectations. Spark on Dataproc or Vertex AI exposure. Professional Data Engineer certification. BFSI analytics domain knowledge. Benefits & Culture Highlights Modern Bengaluru campus with on-site labs and wellness facilities. Annual GCP certification sponsorship and dedicated learning budget. Performance-linked bonus and accelerated career paths. Skills: vertex ai,data studio,airflow,terraform,ci/cd,spark,beam sdk,bigquery,etl performance tuning,kafka,git,dataproc,data quality tooling,gcp,sql,schema design,java,cost optimization,etl,python,composer,looker,pub/sub

Key Responsibilities Design, develop, and maintain scalable web applications using .NET Core, .NET Framework, C#, and related technologies. Participate in all phases of the SDLC, including requirements gathering, architecture design, coding, testing, deployment, and support. Build and integrate RESTful APIs, and work with SQL Server, Entity Framework, and modern front-end technologies such as Angular, React, and JavaScript. Conduct thorough code reviews, write unit tests, and ensure adherence to coding standards and best practices. Lead or support .NET Framework to .NET Core migration initiatives, ensuring minimal disruption and optimal performance. Implement and manage CI/CD pipelines using tools like Azure DevOps, Jenkins, or GitLab CI/CD. Containerize applications using Docker and deploy/manage them on orchestration platforms like Kubernetes or GKE. Lead and execute database migration projects, particularly transitioning from SQL Server to PostgreSQL. Manage and optimize Cloud SQL for PostgreSQL, including configuration, tuning, and ongoing maintenance. Leverage Google Cloud Platform (GCP) services such as GKE, Cloud SQL, Cloud Run, and Dataflow to build and maintain cloud-native solutions. Handle schema conversion and data transformation tasks as part of migration and modernization efforts. Required Skills & Experience 5+ years of hands-on experience with C#, .NET Core, and .NET Framework. Proven experience in application modernization and cloud-native development. Strong knowledge of containerization (Docker) and orchestration tools like Kubernetes/GKE. Expertise in implementing and managing CI/CD pipelines. Solid understanding of relational databases and experience in SQL Server to PostgreSQL migrations. Familiarity with cloud infrastructure, especially GCP services relevant to application hosting and data processing. Excellent problem-solving, communication, Skills:- C#, .NET, .NET Compact Framework, SQL, Microsoft Windows Azure, CI/CD, Google Cloud Platform (GCP), React.js and Data-flow analysis

Job Description: We are looking for a highly skilled Engineer with a solid experience of building Bigdata, GCP Cloud based real time data pipelines and REST APIs with Java frameworks. The Engineer will play a crucial role in designing, implementing, and optimizing data solutions to support our organization s data-driven initiatives. This role requires expertise in data engineering, strong problem-solving abilities, and a collaborative mindset to work effectively with various stakeholders. This role will be focused on the delivery of innovative solutions to satisfy the needs of our business. As an agile team we work closely with our business partners to understand what they require, and we strive to continuously improve as a team. Technical Skills 1. Core Data Engineering Skills Proficiency in using GCP s big data tools like BigQuery For data warehousing and SQL analytics. Dataproc: For running Spark and Hadoop clusters. GCP Dataflow For stream and batch data processing.(High level Idea) GCP Pub/Sub: For real-time messaging and event ingestion.(High level Idea) Expertise in building automated, scalable, and reliable pipelines using custom Python/Scala solutions or Cloud Data Functions . 2. Programming and Scripting Strong coding skills in SQL, and Java. Familiarity with APIs and SDKs for GCP services to build custom data solutions. 3. Cloud Infrastructure Understanding of GCP services such as Cloud Storage, Compute Engine, and Cloud Functions. Familiarity with Kubernetes (GKE) and containerization for deploying data pipelines. (Optional but Good to have) 4. DevOps and CI/CD Experience setting up CI/CD pipelines using Cloud Build, GitHub Actions, or other tools. Monitoring and logging tools like Cloud Monitoring and Cloud Logging for production workflows. 5. Backend Development (Spring Boot & Java) Design and develop RESTful APIs and microservices using Spring Boot. Implement business logic, security, authentication (JWT/OAuth), and database operations. Work with relational databases (MySQL, PostgreSQL, MongoDB, Cloud SQL). Optimize backend performance, scalability, and maintainability. Implement unit testing and integration testing Big Data ETL - Datawarehousing GCP Java RESTAPI CI/CD Kubernetes About Virtusa Teamwork, quality of life, professional and personal development: values that Virtusa is proud to embody. When you join us, you join a team of 27,000 people globally that cares about your growth — one that seeks to provide you with exciting projects, opportunities and work with state of the art technologies throughout your career with us. Great minds, great potential: it all comes together at Virtusa. We value collaboration and the team environment of our company, and seek to provide great minds with a dynamic place to nurture new ideas and foster excellence. Virtusa was founded on principles of equal opportunity for all, and so does not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, non-disqualifying physical or mental disability, national origin, veteran status or any other basis covered by appropriate law. All employment is decided on the basis of qualifications, merit, and business need.

Summary We are seeking a highly skilled and motivated GCP Data Engineering Manager to join our dynamic team. As a Data Engineering manager specializing in Google Cloud Platform (GCP), you will play a crucial role in designing, implementing, and maintaining scalable data pipelines and systems. You will leverage your expertise in Google Big Query, SQL, Python, and analytical skills to drive data-driven decision-making processes and support various business functions. About The Role Key Responsibilities: Data Pipeline Development: Design, develop, and maintain robust data pipelines using GCP services like Dataflow, Dataproc, ensuring high performance and scalability. Google Big Query Expertise: Utilize your hands-on experience with Google Big Query to manage and optimize data storage, retrieval, and processing. SQL Proficiency: Write and optimize complex SQL queries to transform and analyze large datasets, ensuring data accuracy and integrity. Python Programming: Develop and maintain Python scripts for data processing, automation, and integration with other systems and tools. Data Integration: Collaborate with data analysts, and other stakeholders to integrate data from various sources, ensuring seamless data flow and consistency. Data Quality and Governance: Implement data quality checks, validation processes, and governance frameworks to maintain high data standards. Performance Tuning: Monitor and optimize the performance of data pipelines, queries, and storage solutions to ensure efficient data processing. Documentation: Create comprehensive documentation for data pipelines, processes, and best practices to facilitate knowledge sharing and team collaboration. Minimum Qualifications Proven experience (minimum 6 – 8 yrs) in Data Engineer, with significant hands-on experience in Google Cloud Platform (GCP) and Google Big Query. Proficiency in SQL for data transformation, analysis and performance optimization. Strong programming skills in Python, with experience in developing data processing scripts and automation. Proven analytical skills with the ability to interpret complex data and provide actionable insights. Excellent problem-solving abilities and attention to detail. Strong communication and collaboration skills, with the ability to work effectively in a team enviro Desired Skills Experience with Google Analytics data and understanding of digital marketing data. Familiarity with other GCP services such as Cloud Storage, Dataflow, Pub/Sub, and Dataproc. Knowledge of data visualization tools such as Looker, Tableau, or Data Studio. Experience with machine learning frameworks and libraries. Why Novartis: Helping people with disease and their families takes more than innovative science. It takes a community of smart, passionate people like you. Collaborating, supporting and inspiring each other. Combining to achieve breakthroughs that change patients’ lives. Ready to create a brighter future together? https://www.novartis.com/about/strategy/people-and-culture Join our Novartis Network: Not the right Novartis role for you? Sign up to our talent community to stay connected and learn about suitable career opportunities as soon as they come up: https://talentnetwork.novartis.com/network Benefits and Rewards: Read our handbook to learn about all the ways we’ll help you thrive personally and professionally: https://www.novartis.com/careers/benefits-rewards

The purpose of this role is to understand, model and facilitate change in a significant area of the business and technology portfolio either by line of business, geography or specific architecture domain whilst building the overall Architecture capability and knowledge base of the company. Job Description: Role Overview : We are seeking a highly skilled and motivated Cloud Data Engineering Manager to join our team. The role is critical to the development of a cutting-edge reporting platform designed to measure and optimize online marketing campaigns. The GCP Data Engineering Manager will design, implement, and maintain scalable, reliable, and efficient data solutions on Google Cloud Platform (GCP). The role focuses on enabling data-driven decision-making by developing ETL/ELT pipelines, managing large-scale datasets, and optimizing data workflows. The ideal candidate is a proactive problem-solver with strong technical expertise in GCP, a passion for data engineering, and a commitment to delivering high-quality solutions aligned with business needs. Key Responsibilities : Data Engineering & Development : Design, build, and maintain scalable ETL/ELT pipelines for ingesting, processing, and transforming structured and unstructured data. Implement enterprise-level data solutions using GCP services such as BigQuery, Dataform, Cloud Storage, Dataflow, Cloud Functions, Cloud Pub/Sub, and Cloud Composer. Develop and optimize data architectures that support real-time and batch data processing. Build, optimize, and maintain CI/CD pipelines using tools like Jenkins, GitLab, or Google Cloud Build. Automate testing, integration, and deployment processes to ensure fast and reliable software delivery. Cloud Infrastructure Management : Manage and deploy GCP infrastructure components to enable seamless data workflows. Ensure data solutions are robust, scalable, and cost-effective, leveraging GCP best practices. Infrastructure Automation and Management: Design, deploy, and maintain scalable and secure infrastructure on GCP. Implement Infrastructure as Code (IaC) using tools like Terraform. Manage Kubernetes clusters (GKE) for containerized workloads. Collaboration and Stakeholder Engagement : Work closely with cross-functional teams, including data analysts, data scientists, DevOps, and business stakeholders, to deliver data projects aligned with business goals. Translate business requirements into scalable, technical solutions while collaborating with team members to ensure successful implementation. Quality Assurance & Optimization : Implement best practices for data governance, security, and privacy, ensuring compliance with organizational policies and regulations. Conduct thorough quality assurance, including testing and validation, to ensure the accuracy and reliability of data pipelines. Monitor and optimize pipeline performance to meet SLAs and minimize operational costs. Qualifications and Certifications : Education: Bachelor’s or master’s degree in computer science, Information Technology, Engineering, or a related field. Experience: Minimum of 7 to 9 years of experience in data engineering, with at least 4 years working on GCP cloud platforms. Proven experience designing and implementing data workflows using GCP services like BigQuery, Dataform Cloud Dataflow, Cloud Pub/Sub, and Cloud Composer. Certifications: Google Cloud Professional Data Engineer certification preferred. Key Skills : Mandatory Skills: Advanced proficiency in Python for data pipelines and automation. Strong SQL skills for querying, transforming, and analyzing large datasets. Strong hands-on experience with GCP services, including Cloud Storage, Dataflow, Cloud Pub/Sub, Cloud SQL, BigQuery, Dataform, Compute Engine and Kubernetes Engine (GKE). Hands-on experience with CI/CD tools such as Jenkins, GitHub or Bitbucket. Proficiency in Docker, Kubernetes, Terraform or Ansible for containerization, orchestration, and infrastructure as code (IaC) Familiarity with workflow orchestration tools like Apache Airflow or Cloud Composer Strong understanding of Agile/Scrum methodologies Nice-to-Have Skills: Experience with other cloud platforms like AWS or Azure. Knowledge of data visualization tools (e.g., Power BI, Looker, Tableau). Understanding of machine learning workflows and their integration with data pipelines. Soft Skills : Strong problem-solving and critical-thinking abilities. Excellent communication skills to collaborate with technical and non-technical stakeholders. Proactive attitude towards innovation and learning. Ability to work independently and as part of a collaborative team. Location: Bengaluru Brand: Merkle Time Type: Full time Contract Type: Permanent

Principal Data Engineer _ Hyderabad (Onsite) Job Title. Principal Data Engineer Work Location. Hyderabad (Onsite) Experience. 10+ Years Job Description: 10+ years of experience in data engineering, with at least 3 years in a technical leadership role. Strong expertise in SQL, Python or Scala, and modern ETL/ELT frameworks. Deep knowledge of data warehousing solutions (e.g., Snowflake, Redshift, BigQuery) and distributed systems (e.g., Hadoop, Spark). Proven experience with cloud platforms (AWS, Azure, or GCP) and associated data services (e.g., S3, Glue, Dataflow, Databricks). Hands-on experience with streaming platforms such as Kafka, Flink, or Kinesis. Solid understanding of data modeling, data lakes, data governance, and security. Excellent communication, leadership, and stakeholder management skills. Preferred Qualifications: Exposure to tools like Airflow, dbt, Terraform, or Kubernetes. Familiarity with data cataloging and lineage tools (e.g., Alation, Collibra). Domain experience in [e.g., Banking, Healthcare, Finance, E-commerce] is a plus. Experience in designing data platforms for AI/ML workloads.

Syensqo is all about chemistry. We’re not just referring to chemical reactions here, but also to the magic that occurs when the brightest minds get to work together. This is where our true strength lies. In you. In your future colleagues and in all your differences. And of course, in your ideas to improve lives while preserving our planet’s beauty for the generations to come. Join us at Syensqo, where our IT team is gearing up to enhance its capabilities. We play a crucial role in the group's transformation—accelerating growth, reshaping progress, and creating sustainable shared value. IT team is making operational adjustments to supercharge value across the entire organization. Here at Syensqo, we're one strong team! Our commitment to accountability drives us as we work hard to deliver value for our customers and stakeholders. In our dynamic and collaborative work environment, we add a touch of enjoyment while staying true to our motto: reinvent progress. Come be part of our transformation journey and contribute to the change as a future team member. We are looking for: As a Data/ML Engineer, you will play a central role in defining, implementing, and maintaining cloud governance frameworks across the organization. You will collaborate with cross-functional teams to ensure secure, compliant, and efficient use of cloud resources for data and machine learning workloads. Your expertise in full-stack automation, DevOps practices, and Infrastructure as Code (IaC) will drive the standardization and scalability of our cloud-based data and ML platforms. Key requirements are: Ensuring cloud data governance Define and maintain central cloud governance policies, standards, and best practices for data, AI and ML workloads Ensure compliance with security, privacy, and regulatory requirements across all cloud environments Monitor and optimize cloud resource usage, cost, and performance for data, AI and ML workloads Design and Implement Data Pipelines Co-develop, co-construct, test, and maintain highly scalable and reliable data architectures, including ETL processes, data warehouses, and data lakes with the Data Platform Team Build and Deploy ML Systems Co-design, co-develop, and deploy machine learning models and associated services into production environments, ensuring performance, reliability, and scalability Infrastructure Management Manage and optimize cloud-based infrastructure (e.g., AWS, Azure, GCP) for data storage, processing, and ML model serving Collaboration Work collaboratively with data scientists, ML engineers, security and business stakeholders to align cloud governance with organizational needs Provide guidance and support to teams on cloud architecture, data management, and ML operations. Work collaboratively with other teams to transition prototypes and experimental models into robust, production-ready solutions Data Governance and Quality: Implement best practices for data governance, data quality, and data security to ensure the integrity and reliability of our data assets. Performance and Optimisation: Identify and implement performance improvements for data pipelines and ML models, optimizing for speed, cost-efficiency, and resource utilization. Monitoring and Alerting Establish and maintain monitoring, logging, and alerting systems for data pipelines and ML models to proactively identify and resolve issues Tooling and Automation Design and implement full-stack automation for data pipelines, ML workflows, and cloud infrastructure Build and manage cloud infrastructure using IaC tools (e.g., Terraform, CloudFormation) Develop and maintain CI/CD pipelines for data and ML projects Promote DevOps culture and best practices within the organization Develop and maintain tools and automation scripts to streamline data operations, model training, and deployment processes Stay Current on new ML / AI trends: Keep abreast of the latest advancements in data engineering, machine learning, and cloud technologies, evaluating and recommending new tools and approach Document processes, architectures, and standards for knowledge sharing and onboarding Education and experience Education: Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related quantitative field. (Relevant work experience may be considered in lieu of a degree). Programming: Strong proficiency in Python (essential) and experience with other relevant languages like Java, Scala, or Go. Data Warehousing/Databases: Solid understanding and experience with relational databases (e.g., PostgreSQL, MySQL) and NoSQL databases (e.g., MongoDB, Cassandra). Experience with data warehousing solutions (e.g., Snowflake, Redshift, BigQuery) is highly desirable. Big Data Technologies: Hands-on experience with big data processing frameworks (e.g., Spark, Flink, Hadoop). Cloud Platforms: Experience with at least one major cloud provider (AWS, Azure, or GCP) and their relevant data and ML services (e.g., S3, EC2, Lambda, EMR, SageMaker, Dataflow, BigQuery, Azure Data Factory, Azure ML). ML Concepts: Fundamental understanding of machine learning concepts, algorithms, and workflows. MLOps Principles: Familiarity with MLOps principles and practices for deploying, monitoring, and managing ML models in production. Version Control: Proficiency with Git and collaborative development workflows. Problem-Solving: Excellent analytical and problem-solving skills with a strong attention to detail. Communication: Strong communication skills, able to articulate complex technical concepts to both technical and non-technical stakeholders. Bonus Points (Highly Desirable Skills & Experience): Experience with containerisation technologies (Docker, Kubernetes). Familiarity with CI/CD pipelines for data and ML deployments. Experience with stream processing technologies (e.g., Kafka, Kinesis). Knowledge of data visualization tools (e.g., Tableau, Power BI, Looker). Contributions to open-source projects or a strong portfolio of personal projects. Experience with [specific domain knowledge relevant to your company, e.g., financial data, healthcare data, e-commerce data]. Language skills Fluent English What’s in it for the candidate Be part of a highly motivated team of explorers Help make a difference and thrive in Cloud and AI technology Chart your own course and build a fantastic career Have fun and enjoy life with an industry leading remuneration pack About Us Syensqo is a science company developing groundbreaking solutions that enhance the way we live, work, travel and play. Inspired by the scientific councils which Ernest Solvay initiated in 1911, we bring great minds together to push the limits of science and innovation for the benefit of our customers, with a diverse, global team of more than 13,000 associates. Our solutions contribute to safer, cleaner, and more sustainable products found in homes, food and consumer goods, planes, cars, batteries, smart devices and health care applications. Our innovation power enables us to deliver on the ambition of a circular economy and explore breakthrough technologies that advance humanity. At Syensqo, we seek to promote unity and not uniformity. We value the diversity that individuals bring and we invite you to consider a future with us, regardless of background, age, gender, national origin, ethnicity, religion, sexual orientation, ability or identity. We encourage individuals who may require any assistance or accommodations to let us know to ensure a seamless application experience. We are here to support you throughout the application journey and want to ensure all candidates are treated equally. If you are unsure whether you meet all the criteria or qualifications listed in the job description, we still encourage you to apply.

Job Description We are looking for a highly skilled Engineer with a solid experience of building Bigdata, GCP Cloud based real time data pipelines and REST APIs with Java frameworks. The Engineer will play a crucial role in designing, implementing, and optimizing data solutions to support our organization s data-driven initiatives. This role requires expertise in data engineering, strong problem-solving abilities, and a collaborative mindset to work effectively with various stakeholders. This role will be focused on the delivery of innovative solutions to satisfy the needs of our business. As an agile team we work closely with our business partners to understand what they require, and we strive to continuously improve as a team. Technical Skills 1. Core Data Engineering Skills Proficiency in using GCP s big data tools like BigQuery For data warehousing and SQL analytics. Dataproc: For running Spark and Hadoop clusters. GCP Dataflow For stream and batch data processing.(High level Idea) GCP Pub/Sub: For real-time messaging and event ingestion.(High level Idea) Expertise in building automated, scalable, and reliable pipelines using custom Python/Scala solutions or Cloud Data Functions . Programming and Scripting Strong coding skills in SQL, and Java. Familiarity with APIs and SDKs for GCP services to build custom data solutions. Cloud Infrastructure Understanding of GCP services such as Cloud Storage, Compute Engine, and Cloud Functions. Familiarity with Kubernetes (GKE) and containerization for deploying data pipelines. (Optional but Good to have) DevOps and CI/CD Experience setting up CI/CD pipelines using Cloud Build, GitHub Actions, or other tools. Monitoring and logging tools like Cloud Monitoring and Cloud Logging for production workflows. Backend Development (Spring Boot & Java) Design and develop RESTful APIs and microservices using Spring Boot. Implement business logic, security, authentication (JWT/OAuth), and database operations. Work with relational databases (MySQL, PostgreSQL, MongoDB, Cloud SQL). Optimize backend performance, scalability, and maintainability. Implement unit testing and integration testing Big Data ETL - Datawarehousing GCP Java RESTAPI CI/CD Kubernetes