14 Data Lakehouse Jobs

FICO is a leading global analytics software company that assists businesses in over 100 countries in making informed decisions. By joining the world-class team at FICO, you will have the opportunity to realize your career potential. As a part of the product development team, you will play a crucial role in providing thought leadership and driving innovation. This position involves collaborating closely with product management to architect, design, and develop a highly feature-rich product as the VP, Software Engineering. Your responsibilities will include designing, developing, testing, deploying, and supporting the capabilities of a large enterprise-level platform. You will create scalable microservices with a focus on high performance, availability, interoperability, and reliability. Additionally, you will contribute to technical designs, participate in defining technical acceptance criteria, and mentor junior engineers to uphold quality standards. To be successful in this role, you should hold a Bachelor's or Master's degree in computer science or a related field and possess a minimum of 7 years of experience in software architecture, design, development, and testing. Expertise in Java, Spring, Spring Boot, Maven/Gradle, Docker, Git, GitHub, as well as experience with data structures, algorithms, and system design is essential. Furthermore, you should have a strong understanding of microservices architecture, RESTful and gRPC APIs, cloud engineering technologies such as Kubernetes and AWS/Azure/GCP, and databases like MySQL, PostgreSQL, MongoDB, and Cassandra. Experience with Agile software development, data engineering services, and software design principles is highly desirable. At FICO, you will have the opportunity to work in an inclusive culture that values core principles like acting like an owner, delighting customers, and earning respect. You will benefit from competitive compensation, benefits, and rewards programs while enjoying a people-first work environment that promotes work/life balance and professional development. Join FICO and be part of a leading organization at the forefront of Big Data analytics, where you can contribute to helping businesses leverage data to enhance decision-making processes. Your role at FICO will make a significant impact on global businesses, and you will be part of a diverse and inclusive environment that fosters collaboration and innovation.,

The ideal candidate for this position should have advanced proficiency in Python, with a solid understanding of inheritance and classes. Additionally, the candidate should be well-versed in EMR, Athena, Redshift, AWS Glue, IAM roles, CloudFormation (CFT is optional), Apache Airflow, Git, SQL, Py-Spark, Open Metadata, and Data Lakehouse. Experience with metadata management is highly desirable, particularly with AWS Services such as S3. The candidate should possess the following key skills: - Creation of ETL Pipelines - Deploying code in EMR - Querying in Athena - Creating Airflow Dags for scheduling ETL pipelines - Knowledge of AWS Lambda and ability to create Lambda functions This role is for an individual contributor, and as such, the candidate is expected to autonomously manage client communication and proactively resolve technical issues without external assistance.,

A leading player in cloud-based enterprise solutions is expanding its analytics leadership team in Bangalore. This pivotal role calls for a seasoned professional to drive the evolution of data products and analytics capabilities across international markets. The ideal candidate will possess the strategic vision, technical expertise, and stakeholder savvy to lead in a fast-paced, innovation-driven environment. Key Responsibilities Lead and mentor a dynamic team of product managers to scale enterprise-grade data lake and analytics platforms Drive program execution and delivery with a focus on performance, prioritization, and business alignment Define and execute the roadmap for an analytical data platform, ensuring alignment with strategic and user-centric goals Collaborate cross-functionally with engineering, design, and commercial teams to launch impactful BI solutions Translate complex business needs into scalable data models and actionable product requirement documents for multi-tenant SaaS products Champion AI-enabled analytics experiences to deliver smart, context-aware data workflows Maintain high standards in performance, usability, trust, and documentation of data products Ensure seamless execution of global data strategies through on-the-ground leadership in India Promote agile methodologies, metadata governance, and product-led thinking across teams Ideal Candidate Profile 10+ years in product leadership roles focused on data products, BI, or analytics in SaaS environments Deep understanding of modern data architectures, including dimensional modeling and cloud-native analytics tools Proven expertise in building multi-tenant data platforms serving external customer use cases Skilled in simplifying complex inputs into clear, scalable requirements and deliverables Familiarity with platforms like Deltalake, dbt, ThoughtSpot, and similar tools Strong communicator with demonstrated stakeholder management and team leadership capabilities Experience launching customer-facing analytics products is a definite plus A passion for intuitive, scalable, and intelligent user experiences powered by data

Experience in ETL and Data Warehousing Excellent leadership and communication skills Strong hands-on experience with Data Lakehouse architecture Proficient in GCP BigQuery, Cloud Storage, Airflow, Dataflow, Cloud Functions, Pub/Sub, Cloud Run Built solution automations using various ETL tools Delivered at least 2 GCP Cloud Data Warehousing projects Worked on at least 2 Agile/SAFe methodology-based projects Experience with PySpark and Teradata Skilled in using DevOps tools like GitHub, Jenkins, Cloud Native tools Experienced in handling semi-structured data formats like JSON, Parquet, XML Written complex SQL queries for data analysis and extraction Deep understanding of Data Warehousing, Data Analysis, Data Profiling, Data Quality, and Data Mapping Global delivery model experience (15+ team members) Collaborated with product/project managers, developers, DBAs, and data governance teams for requirements, design, and deployment Responsibilities: Design and implement data pipelines using GCP services Manage deployments and ensure efficient orchestration of services Implement CI/CD pipelines using Jenkins or native tools Guide a team of data engineers in building scalable data pipelines Develop ETL/ELT pipelines using Python, Beam, and SQL Continuously monitor and optimize data workflows Integrate data from various sources using GCP services and orchestrate with Cloud Composer (Airflow) Set up monitoring and alerting using Cloud Monitoring, Datadog, etc. Mentor junior developers and data engineers Collaborate with developers, architects, and stakeholders on robust data solutions Lead data migration from legacy systems (Oracle, Teradata, SQL Server) to GCP Facilitate Agile ceremonies (sprint planning, scrums, backlog grooming) Interact with clients on analytics programs and ensure governance and communication with program leadership

Good experience in Apache Iceberg, Apache Spark, Trino Proficiency in SQL and data modeling Experience with open Data Lakehouse using Apache Iceberg Experience with Data Lakehouse architecture with Apache Iceberg and Trino Design and implement scalable Data Lakehouse solutions using Apache Iceberg and Trino to optimize data storage and query performance.

Azure Cloud Data Lead Job Title: Azure Cloud Data Lead Location: Pune, India Experience: 7 - 12 Years Work Mode: Full-time, Office-based Company Overview : Smartavya Analytica is a niche Data and AI company based in Mumbai, established in 2017. We specialize in data-driven innovation, transforming enterprise data into strategic insights. With expertise spanning over 25+ Data Modernization projects and handling large datasets up to 24 PB in a single implementation, we have successfully delivered data and AI projects across multiple industries, including retail, finance, telecom, manufacturing, insurance, and capital markets. We are specialists in Cloud, Hadoop, Big Data, AI, and Analytics, with a strong focus on Data Modernization for On-premises, Private, and Public Cloud Platforms. Visit us at: https://smart-analytica.com Job Summary: We are looking for a highly experienced Azure Cloud Data Lead to oversee the architecture, design, and delivery of enterprise-scale cloud data solutions. This role demands deep expertise in Azure Data Services , strong hands-on experience with data engineering and governance , and a strategic mindset to guide cloud modernization initiatives across complex environments. Key Responsibilities: Architect and design data lakehouses , data warehouses , and analytics platforms using Azure Data Services . Lead implementations using Azure Data Factory (ADF) , Azure Synapse Analytics , and Azure Fabric (OneLake ecosystem). Define and implement data governance frameworks including cataloguing, lineage, security, and quality controls. Collaborate with business stakeholders, data engineers, and developers to translate business requirements into scalable Azure architectures. Ensure platform design meets performance, scalability, security, and regulatory compliance needs. Guide migration of on-premises data platforms to Azure Cloud environments. Create architectural artifacts: solution blueprints, reference architectures, governance models, and best practice guidelines. Collaborate with Sales / presales to customer meetings to understand the business requirement, the scope of work and propose relevant solutions. Drive the MVP/PoC and capability demos to prospective customers / opportunities Must-Have Skills: 7 - 12 years of experience in data architecture, data engineering, or analytics solutions. Hands-on expertise in Azure Cloud services: ADF , Synapse , Azure Fabric (OneLake) , and Databricks (good to have). Strong understanding of data governance , metadata management, and compliance frameworks (e.g., GDPR, HIPAA). Deep knowledge of relational and non-relational databases (SQL, NoSQL) on Azure. Experience with security practices (IAM, RBAC, encryption, data masking) in cloud environments. Strong client-facing skills with the ability to present complex solutions clearly. Preferred Certifications: Microsoft Certified: Azure Solutions Architect Expert Microsoft Certified: Azure Data Engineer Associate

Overview Deputy Director - Data Engineering PepsiCo operates in an environment undergoing immense and rapid change. Big-data and digital technologies are driving business transformation that is unlocking new capabilities and business innovations in areas like eCommerce, mobile experiences and IoT. The key to winning in these areas is being able to leverage enterprise data foundations built on PepsiCos global business scale to enable business insights, advanced analytics, and new product development. PepsiCos Data Management and Operations team is tasked with the responsibility of developing quality data collection processes, maintaining the integrity of our data foundations, and enabling business leaders and data scientists across the company to have rapid access to the data they need for decision-making and innovation. Increase awareness about available data and democratize access to it across the company. As a data engineering lead, you will be the key technical expert overseeing PepsiCo's data product build & operations and drive a strong vision for how data engineering can proactively create a positive impact on the business. You'll be empowered to create & lead a strong team of data engineers who build data pipelines into various source systems, rest data on the PepsiCo Data Lake, and enable exploration and access for analytics, visualization, machine learning, and product development efforts across the company. As a member of the data engineering team, you will help lead the development of very large and complex data applications into public cloud environments directly impacting the design, architecture, and implementation of PepsiCo's flagship data products around topics like revenue management, supply chain, manufacturing, and logistics. You will work closely with process owners, product owners and business users. You'll be working in a hybrid environment with in-house, on-premises data sources as well as cloud and remote systems. Responsibilities Data engineering lead role for D&Ai data modernization (MDIP) Ideally Candidate must be flexible to work an alternative schedule either on tradition work week from Monday to Friday; or Tuesday to Saturday or Sunday to Thursday depending upon coverage requirements of the job. The candidate can work with immediate supervisor to change the work schedule on rotational basis depending on the product and project requirements. Responsibilities Manage a team of data engineers and data analysts by delegating project responsibilities and managing their flow of work as well as empowering them to realize their full potential. Design, structure and store data into unified data models and link them together to make the data reusable for downstream products. Manage and scale data pipelines from internal and external data sources to support new product launches and drive data quality across data products. Create reusable accelerators and solutions to migrate data from legacy data warehouse platforms such as Teradata to Azure Databricks and Azure SQL. Enable and accelerate standards-based development prioritizing reuse of code, adopt test-driven development, unit testing and test automation with end-to-end observability of data Build and own the automation and monitoring frameworks that captures metrics and operational KPIs for data pipeline quality, performance and cost. Collaborate with internal clients (product teams, sector leads, data science teams) and external partners (SI partners/data providers) to drive solutioning and clarify solution requirements. Evolve the architectural capabilities and maturity of the data platform by engaging with enterprise architects to build and support the right domain architecture for each application following well-architected design standards. Define and manage SLAs for data products and processes running in production. Create documentation for learnings and knowledge transfer to internal associates. Qualifications 12+ years of engineering and data management experience Qualifications 12+ years of overall technology experience that includes at least 5+ years of hands-on software development, data engineering, and systems architecture. 8+ years of experience with Data Lakehouse, Data Warehousing, and Data Analytics tools. 6+ years of experience in SQL optimization and performance tuning on MS SQL Server, Azure SQL or any other popular RDBMS 6+ years of experience in Python/Pyspark/Scala programming on big data platforms like Databricks 4+ years in cloud data engineering experience in Azure or AWS. Fluent with Azure cloud services. Azure Data Engineering certification is a plus. Experience with integration of multi cloud services with on-premises technologies. Experience with data modelling, data warehousing, and building high-volume ETL/ELT pipelines. Experience with data profiling and data quality tools like Great Expectations. Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets. Experience with at least one business intelligence tool such as Power BI or Tableau Experience with running and scaling applications on the cloud infrastructure and containerized services like Kubernetes. Experience with version control systems like ADO, Github and CI/CD tools for DevOps automation and deployments. Experience with Azure Data Factory, Azure Databricks and Azure Machine learning tools. Experience with Statistical/ML techniques is a plus. Experience with building solutions in the retail or in the supply chain space is a plus. Understanding of metadata management, data lineage, and data glossaries is a plus. BA/BS in Computer Science, Math, Physics, or other technical fields. Candidate must be flexible to work an alternative work schedule either on tradition work week from Monday to Friday; or Tuesday to Saturday or Sunday to Thursday depending upon product and project coverage requirements of the job. Candidates are expected to be in the office at the assigned location at least 3 days a week and the days at work needs to be coordinated with immediate supervisor Skills, Abilities, Knowledge: Excellent communication skills, both verbal and written, along with the ability to influence and demonstrate confidence in communications with senior level management. Proven track record of leading, mentoring data teams. Strong change manager. Comfortable with change, especially that which arises through company growth. Ability to understand and translate business requirements into data and technical requirements. High degree of organization and ability to manage multiple, competing projects and priorities simultaneously. Positive and flexible attitude to enable adjusting to different needs in an ever-changing environment. Strong leadership, organizational and interpersonal skills; comfortable managing trade-offs. Foster a team culture of accountability, communication, and self-management. Proactively drives impact and engagement while bringing others along. Consistently attain/exceed individual and team goals. Ability to lead others without direct authority in a matrixed environment. Comfortable working in a hybrid environment with teams consisting of contractors as well as FTEs spread across multiple PepsiCo locations. Domain Knowledge in CPG industry with Supply chain/GTM background is preferred.

We are seeking a highly skilled and experienced Data Architect with strong expertise in data modeling and Snowflake to design, develop, and optimize enterprise data architecture. The ideal candidate will play a critical role in shaping data strategy, building scalable models, and ensuring efficient data integration and governance. Key Responsibilities: Design and implement end-to-end data architecture using Snowflake Develop and maintain conceptual, logical, and physical data models. Define and enforce data architecture standards, best practices, and policies. Collaborate with data engineers, analysts, and business stakeholders to gather requirements and design data solutions. Optimize Snowflake performance including data partitioning, caching, and query tuning. Create and manage data dictionaries, metadata, and lineage documentation. Ensure data quality, consistency, and security across all data platforms. Support data integration from various sources (cloud/on-premises) into Snowflake. Required Skills and Experience: 8+ years of experience in data architecture, data modeling, or similar roles. Hands-on expertise with Snowflake including Snowpipe, Streams, Tasks, and Secure Data Sharing. Strong experience with data modeling tools (e.g., Erwin, ER/Studio, dbt). Proficiency in SQL , ETL/ELT pipelines , and data warehousing concepts . Experience working with structured, semi-structured (JSON, XML), and unstructured data. Solid understanding of data governance, data cataloging, and security frameworks. Excellent analytical, communication, and stakeholder management skills. Preferred Qualifications: Experience with cloud platforms like AWS , Azure , or GCP . Familiarity with data lakehouse architecture and real-time data processing. Snowflake Certification(s) or relevant cloud certifications. Knowledge of Python or scripting for data automation is a plus.

We are seeking a highly skilled and experienced Data Architect with strong expertise in data modeling and Snowflake to design, develop, and optimize enterprise data architecture. The ideal candidate will play a critical role in shaping data strategy, building scalable models, and ensuring efficient data integration and governance. Key Responsibilities: Design and implement end-to-end data architecture using Snowflake Develop and maintain conceptual, logical, and physical data models. Define and enforce data architecture standards, best practices, and policies. Collaborate with data engineers, analysts, and business stakeholders to gather requirements and design data solutions. Optimize Snowflake performance including data partitioning, caching, and query tuning. Create and manage data dictionaries, metadata, and lineage documentation. Ensure data quality, consistency, and security across all data platforms. Support data integration from various sources (cloud/on-premises) into Snowflake. Required Skills and Experience: 8+ years of experience in data architecture, data modeling, or similar roles. Hands-on expertise with Snowflake including Snowpipe, Streams, Tasks, and Secure Data Sharing. Strong experience with data modeling tools (e.g., Erwin, ER/Studio, dbt). Proficiency in SQL , ETL/ELT pipelines , and data warehousing concepts . Experience working with structured, semi-structured (JSON, XML), and unstructured data. Solid understanding of data governance, data cataloging, and security frameworks. Excellent analytical, communication, and stakeholder management skills. Preferred Qualifications: Experience with cloud platforms like AWS , Azure , or GCP . Familiarity with data lakehouse architecture and real-time data processing. Snowflake Certification(s) or relevant cloud certifications. Knowledge of Python or scripting for data automation is a plus.

Azure Cloud Data Solutions Architect Job Title: Azure Cloud Data Solutions Architect Location: Pune, India Experience: 10 - 15 Years Work Mode: Full-time, Office-based Company : Smartavya Analytica Private Limited Company Overview: Smartavya Analytica is a niche Data and AI company based in Mumbai, established in 2017. We specialize in data-driven innovation, transforming enterprise data into strategic insights. With expertise spanning over 25+ Data Modernization projects and handling large datasets up to 24 PB in a single implementation, we have successfully delivered data and AI projects across multiple industries, including retail, finance, telecom, manufacturing, insurance, and capital markets. We are specialists in Cloud, Hadoop, Big Data, AI, and Analytics, with a strong focus on Data Modernization for On-premises, Private, and Public Cloud Platforms. Visit us at: https://smart-analytica.com Job Summary: We are seeking an experienced Azure Cloud Data Solutions Architect to lead end-to-end architecture and delivery of enterprise-scale cloud data platforms. The ideal candidate will have deep expertise in Azure Data Services , Data Engineering , and Data Governance , with the ability to architect and guide cloud modernization initiatives. Key Responsibilities: Architect and design data lakehouses , data warehouses , and analytics platforms using Azure Data Services . Lead implementations using Azure Data Factory (ADF) , Azure Synapse Analytics , and Azure Fabric (OneLake ecosystem). Define and implement data governance frameworks including cataloguing, lineage, security, and quality controls. Collaborate with business stakeholders, data engineers, and developers to translate business requirements into scalable Azure architectures. Ensure platform design meets performance, scalability, security, and regulatory compliance needs. Guide migration of on-premises data platforms to Azure Cloud environments. Create architectural artifacts: solution blueprints, reference architectures, governance models, and best practice guidelines. Collaborate with Sales / presales to customer meetings to understand the business requirement, the scope of work and propose relevant solutions. Drive the MVP/PoC and capability demos to prospective customers / opportunities Must-Have Skills: 1015 years of experience in data architecture, data engineering, or analytics solutions. Hands-on expertise in Azure Cloud services: ADF , Synapse , Azure Fabric (OneLake) , and Databricks (good to have). Strong understanding of data governance , metadata management, and compliance frameworks (e.g., GDPR, HIPAA). Deep knowledge of relational and non-relational databases (SQL, NoSQL) on Azure. Experience with security practices (IAM, RBAC, encryption, data masking) in cloud environments. Strong client-facing skills with the ability to present complex solutions clearly. Preferred Certifications: Microsoft Certified: Azure Solutions Architect Expert Microsoft Certified: Azure Data Engineer Associate

Role & responsibilities Urgent Hiring for one of the reputed MNC Exp - 5+ Years Location - Pan India Immediate Joiners only Snowflake developer , Pyspark , Python , API, CI/CD , Cloud services ,Azure , Azure Devops Subject: Fw : TMNA SNOWFLAKE POSITION Please share profiles for Snowflake developers having strong Pyspark experience Job Description: Strong hands-on experience in Snowflake development including Streams, Tasks, and Time Travel Deep understanding of Snowpark for Python and its application for data engineering workflows Proficient in PySpark , Spark SQL, and distributed data processing Experience with API development . Proficiency in cloud services (preferably Azure, but AWS/GCP also acceptable) Solid understanding of CI/CD practices and tools like Azure DevOps, GitHub Actions, GitLab, or Jenkins for snowflake. Knowledge of Delta Lake, Data Lakehouse principles, and schema evolution is a plus Preferred candidate profile

Data Architect- (Snowflake AWS Bigdata & DW) Primary Skill Architecting Solutioning both in Snowflake AWS Big Data -Experience in the Snowflake Big Data and Data warehousing space architecting Big data solutions on any cloud platform AWS Preferred. Technical Skills Required- Experience of Architecting Solutioning both in Snowflake AWS Big Data and DW GDPR AWS Snowflake Understanding on Snowflake Cortex for Generative AI Implementation Experience on framework which can help Reduce the Estimation and cost in Repeating work ie Ingestion or Extraction of data Open understand newly introduced feature around Snowflake Look for new approach and solution based on customer standard Understanding Secure coding standard secure data sharing Data clean room Etc Experience on Snowflake and Spark preferred PySpark other Big Data Projects Experience in working on Cloud Implementations AWS ecosystem S3 EC2 Good knowledge of Hadoop ecosystem tools Hive HBase Pig Knowledge of Airflow NiFi Kafka Panda Lamda Snowflake preferable Responsibilities- A Technical Architect defines and owns the technical architecture of systems to deliver business objectives while ensuring quality standards Responsible for highlevel requirement gathering consulting design development and definition of the technical architecture as per business requirements Enable the creation of designs and frameworks for models and validate their adherence with the overall architecture Will be responsible for technically leading the software projects through all stages of the life cycle including responsibility for requirements capture design development and acceptance testing Lead and direct the technical team to do POC to take the critical architectural decision Work with client architects team to complete the architecture Interested candidates share your CV at himani.girnar@alikethoughts.com with below details Candidate's name- Email and Alternate Email ID- Contact and Alternate Contact no- Total exp- Relevant experience- Current Org- Notice period- CCTC- ECTC- Current Location- Preferred Location- Pancard No-

Develop and maintain scalable data pipelines. Collaborate with data scientists and analysts to support business needs. Work with cloud platforms like AWS, Azure, or Google Cloud. Effectively working with cross-functional teams. Data Modelling.

Design, develop, and maintain scalable ETL pipelines, data lakes, and hosting solutions using Azure tools. Ensure data quality, performance optimization, and compliance across hybrid and cloud environments. Required Candidate profile Data engineer with experience in Azure data services, ETL workflows, scripting, and data modeling. Strong collaboration with analytics teams and hands-on pipeline deployment using best practices