61 Presto Jobs - Page 3

Skill & Experience Mandatory Skills: Azure Cloud Platform, Azure services including advanced knowledge of Azure Databricks, Hive Metastore, and Presto, Azure Kubernetes Service (AKS) Terraform, Ansible, Azure DevOps tools, Azure Databricks, GitHub Strong experience with Azure services, including advanced knowledge of Azure Databricks, Hive Metastore, and Presto. Basic understanding of Azure Kubernetes Service (AKS) is required. Proficiency in Terraform and Ansible for infrastructure management is a plus. 4+ years of experience in cloud technologies, including at least 3 years working with Azure Databricks and data management technologies. Demonstrated experience in managing and optimizing large-scale data processing environments. Excellent problem-solving skills with the ability to optimize and manage complex cloud environments. Proficiency in using Azure DevOps for CI/CD pipelines and GitHub for version control. Microsoft Certified: Azure Solutions Architect Expert (AZ-305) or equivalent advanced certification is preferred. Additional certifications in Azure Databricks or related data technologies are a plus. Azure Databricks Management Hive Metastore Management Presto Operations Automation & CI/CD Optimization & Performance Security & Compliance Documentation & Handoverto-date handover Knowledge Sharingtheir Stakeholder Communication Continuous Improvement

Data Strategy and PlanningDevelop and implement data architecture strategies that align with organizational goals and objectives. Collaborate with business stakeholders to understand data requirements and translate them into actionable plans. Data ModelingDesign and implement logical and physical data models to support business needs. Ensure data models are scalable, efficient, and comply with industry best practices. Database Design and ManagementOversee the design and management of databases, selecting appropriate database technologies based on requirements. Optimize database performance and ensure data integrity and security. Data IntegrationDefine and implement data integration strategies to facilitate seamless flow of information across. Responsibilities: Experience in data architecture and engineering Proven expertise with Snowflake data platform Strong understanding of ETL/ELT processes and data integration Experience with data modeling and data warehousing concepts Familiarity with performance tuning and optimization techniques Excellent problem-solving skills and attention to detail Strong communication and collaboration skills Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Cloud & Data ArchitectureAWS ,Snowflake ETL & Data EngineeringAWS Glue, Apache Spark, Step Functions Big Data & AnalyticsAthena,Presto, Hadoop Database & StorageSQL,Snow sql Security & ComplianceIAM, KMS, Data Masking Preferred technical and professional experience Cloud Data WarehousingSnowflake (Data Modeling, Query Optimization) Data TransformationDBT (Data Build Tool) for ELT pipeline management Metadata & Data GovernanceAlation (Data Catalog, Lineage, Governance)

Job Summary As a Data Engineer at Synechron, you will play a pivotal role in harnessing data to drive business value. Your expertise will be essential in developing and maintaining data pipelines, ensuring data integrity, and facilitating analytics that inform strategic decisions. This role contributes significantly to our business objectives by optimizing data processing and enabling insightful reporting across the organization. Software Requirements Required: AWS Redshift (3+ years of experience) Spark (3+ years of experience) Python (3+ years of experience) Complex SQL (3+ years of experience) Shell scripting (2+ years of experience) Docker (2+ years of experience) Kubernetes (2+ years of experience) Bitbucket (2+ years of experience) Preferred: DBT Dataiku Kubernetes cluster management Overall Responsibilities Develop and optimize data pipelines using big data technologies, ensuring seamless data flow and accessibility. Collaborate with cross-functional teams to translate business requirements into technical solutions. Ensure high data quality and integrity in analytics and reporting processes. Implement data architecture and modeling best practices to support strategic objectives. Troubleshoot and resolve data-related issues, maintaining a service-first mentality to enhance customer satisfaction. Technical Skills (By Category) Programming Languages: EssentialPython, SQL PreferredShell scripting Databases/Data Management: EssentialAWS Redshift, Hive, Presto PreferredDBT Cloud Technologies: EssentialAWS PreferredKubernetes, Docker Frameworks and Libraries: EssentialSpark PreferredDataiku Development Tools and Methodologies: EssentialBitbucket, Airflow or Argo Workflows Experience Requirements 6-7 years of experience in data engineering or related roles. Strong understanding of data & analytics concepts, with proven experience in big data technologies. Experience in the financial services industry preferred but not required. Alternative pathwaysSignificant project experience in data architecture and analytics. Day-to-Day Activities Design and implement scalable data pipelines. Participate in regular team meetings to align on project goals and deliverables. Collaborate with stakeholders to refine data processes and analytics. Make informed decisions on data management strategies and technologies. Qualifications Bachelors degree in Computer Science, Data Engineering, or a related field (or equivalent experience). Certifications in AWS or relevant data engineering technologies preferred. Commitment to continuous professional development in data engineering and analytics. Professional Competencies Strong critical thinking and problem-solving capabilities, with a focus on innovation. Effective communication skills and stakeholder management. Ability to work collaboratively in a team-oriented environment. Adaptability and a willingness to learn new technologies and methodologies. Excellent time and priority management to meet deadlines and project goals.

Data Strategy and PlanningDevelop and implement data architecture strategies that align with organizational goals and objectives. Collaborate with business stakeholders to understand data requirements and translate them into actionable plans. Data ModelingDesign and implement logical and physical data models to support business needs. Ensure data models are scalable, efficient, and comply with industry best practices. Database Design and ManagementOversee the design and management of databases, selecting appropriate database technologies based on requirements. Optimize database performance and ensure data integrity and security. Data IntegrationDefine and implement data integration strategies to facilitate seamless flow of information across. Responsibilities: Experience in data architecture and engineering Proven expertise with Snowflake data platform Strong understanding of ETL/ELT processes and data integration Experience with data modeling and data warehousing concepts Familiarity with performance tuning and optimization techniques Excellent problem-solving skills and attention to detail Strong communication and collaboration skills Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Cloud & Data ArchitectureAWS , Snowflake ETL & Data EngineeringAWS Glue, Apache Spark, Step Functions Big Data & AnalyticsAthena,Presto, Hadoop Database & StorageSQL, Snow sql Security & ComplianceIAM, KMS, Data Masking Preferred technical and professional experience Cloud Data WarehousingSnowflake (Data Modeling, Query Optimization) Data TransformationDBT (Data Build Tool) for ELT pipeline management Metadata & Data GovernanceAlation (Data Catalog, Lineage, Governance

Job Title: Big Data Administrator Location : Hyderabad (Weekly once WFO) Experience : 5+ Years Department : Data Engineering / IT Infrastructure Job Summary: We are seeking a Big Data Administrator with strong expertise in Linux systems, AWS infrastructure, and Big Data technologies. This role is ideal for someone experienced in managing large-scale Hadoop ecosystems in production, with a deep understanding of observability, performance tuning, and automation using tools like Terraform or Ansible. Key Responsibilities: Manage and maintain large-scale Big Data clusters (Cloudera, Hortonworks, or AWS EMR) Develop and support infrastructure as code using Terraform or Ansible Administer Hadoop ecosystem components HDFS, YARN, Hive (Tez, LLAP), Presto, Spark Implement and monitor observability tools like Prometheus, InfluxDB, Dynatrace, Grafana, Splunk Optimize SQL performance on Hive/Spark and understand query plans Automate cluster operations using Python (PySpark) or Shell scripting Support Data Analysts & Scientists with tools like JupyterHub, R-Studio, H2O, SAS Handle data in various formats ORC, Parquet, Avro Integrate with and support Kubernetes-based environments (if applicable) Collaborate across teams for deployments, monitoring, and troubleshooting Must-Have Skills: 5+ years in Linux system administration and AWS cloud infrastructure Experience with Cloudera, Hortonworks, or EMR in production Strong in Terraform / Ansible for automation Solid hands-on with HDFS, YARN, Hive, Spark, Presto Proficient in Python and Shell scripting Familiar with observability tools : Grafana, Prometheus, InfluxDB, Splunk, Dynatrace Familiarity with Active Directory , Windows VDI platforms (Citrix, AWS Workspaces) Nice-to-Have Skills: Experience with Airflow , Oozie Familiar with Pandas, Numpy, Scipy, PyTorch Prior use of Jenkins, Chef, Packer Comfortable reading code in Java, Scala, Python, R Qualifications: Bachelors or Masters degree in Computer Science, Information Technology, or a related field Strong communication, collaboration, and troubleshooting skills Ability to thrive in remote or hybrid work environments Please send your updated resume at komalikab@upwardiq.com

Overview Annalect is seeking a hands-on Data QA Manager to lead and elevate data quality assurance practices across our growing suite of software and data products. This is a technical leadership role embedded within our Technology teams, focused on establishing best-in-class data quality processes that enable trusted, scalable, and high-performance data solutions. As a Data QA Manager, you will drive the design, implementation, and continuous improvement of end-to-end data quality frameworks, with a strong focus on automation, validation, and governance. You will work closely with data engineering, product, and analytics teams to ensure data integrity, accuracy, and compliance across complex data pipelines, platforms, and architectures, including Data Mesh and modern cloud-based ecosystems. This role requires deep technical expertise in SQL, Python, data testing frameworks like Great Expectations, data orchestration tools (Airbyte, DbT, Trino, Starburst), and cloud platforms (AWS, Azure, GCP). You will lead a team of Data QA Engineers while remaining actively involved in solution design, tool selection, and hands-on QA execution. Responsibilities Key Responsibilities: Develop and implement a comprehensive data quality strategy aligned with organizational goals and product development initiatives. Define and enforce data quality standards, frameworks, and best practices, including data validation, profiling, cleansing, and monitoring processes. Establish data quality checks and automated controls to ensure the accuracy, completeness, consistency, and timeliness of data across systems. Collaborate with Data Engineering, Product, and other teams to design and implement scalable data quality solutions integrated within data pipelines and platforms. Define and track key performance indicators (KPIs) to measure data quality and effectiveness of QA processes, enabling actionable insights for continuous improvement. Generate and communicate regular reports on data quality metrics, issues, and trends to stakeholders, highlighting opportunities for improvement and mitigation plans. Maintain comprehensive documentation of data quality processes, procedures, standards, issues, resolutions, and improvements to support organizational knowledge-sharing. Provide training and guidance to cross-functional teams on data quality best practices, fostering a strong data quality mindset across the organization. Lead, mentor, and develop a team of Data QA Analysts/Engineers, promoting a high-performance, collaborative, and innovative culture. Provide thought leadership and subject matter expertise on data quality, influencing technical and business stakeholders toward quality-focused solutions. Continuously evaluate and adopt emerging tools, technologies, and methodologies to advance data quality assurance capabilities and automation. Stay current with industry trends, innovations, and evolving best practices in data quality, data engineering, and analytics to ensure cutting-edge solutions. Qualifications Required Skills 11+ years of hands-on experience in Data Quality Assurance, Data Test Automation, Data Comparison, and Validation across large-scale datasets and platforms. Strong proficiency in SQL for complex data querying, data validation, and data quality investigations across relational and distributed databases. Deep knowledge of data structures, relational and non-relational databases, stored procedures, packages, functions, and advanced data manipulation techniques. Practical experience with leading data quality tools such as Great Expectations, DbT tests, and data profiling and monitoring solutions. Experience with data mesh and distributed data architecture principles for enabling decentralized data quality frameworks. Hands-on experience with modern query engines and data platforms, including Trino/Presto, Starburst, and Snowflake. Experience working with data integration and ETL/ELT tools such as Airbyte, AWS Glue, and DbT for managing and validating data pipelines. Strong working knowledge of Python and related data libraries (e.g., Pandas, NumPy, SQLAlchemy) for building data quality tests and automation scripts.

Job description About the Company : Headquartered in California, U.S.A., GSPANN provides consulting and IT services to global clients. We help clients transform how they deliver business value by helping them optimize their IT capabilities, practices, and operations with our experience in retail, high-technology, and manufacturing. With five global delivery centers and 1900+ employees, we provide the intimacy of a boutique consultancy with the capabilities of a large IT services firm. Role: Senior Data Analyst Experience: 5+ Years Skill Set: Data Analysis, SQL and Cloud (AWS, Azure, GCP) Location: Pune, Hyderabad, Gurgaon Key Requirements: Bachelors degree in Computer Science, MIS, or related fields. 6-7 years of relevant analytical experience, translating strategic vision into actionable requirements. Ability to conduct data analysis, develop and test hypotheses, and deliver insights with minimal supervision. Experience identifying and defining KPIs for business areas such as Sales, Consumer Behavior, Supply Chain, etc. Exceptional SQL skills. Experience with modern visualization tools like Tableau, Power BI, Domo, etc. Knowledge of open-source, big data, and cloud infrastructure such as AWS, Hive, Snowflake, Presto, etc. Incredible attention to detail with a structured problem-solving approach. Excellent communication skills (written and verbal). Experience with agile development methodologies. Experience in retail or e-commerce domains is a plus. How to Apply: Interested candidates can share their CV at pragati.jha@gspann.com.

---- What the Candidate Will Do ---- Partner with engineers, analysts, and product managers to define technical solutions that support business goals Contribute to the architecture and implementation of distributed data systems and platforms Identify inefficiencies in data processing and proactively drive improvements in performance, reliability, and cost Serve as a thought leader and mentor in data engineering best practices across the organization ---- Basic Qualifications ---- 7+ years of hands-on experience in software engineering with a focus on data engineering Proficiency in at least one programming language such as Python, Java, or Scala Strong SQL skills and experience with large-scale data processing frameworks (e.g., Apache Spark, Flink, MapReduce, Presto) Demonstrated experience designing, implementing, and operating scalable ETL pipelines and data platforms Proven ability to work collaboratively across teams and communicate technical concepts to diverse stakeholders ---- Preferred Qualifications ---- Deep understanding of data warehousing concepts and data modeling best practices Hands-on experience with Hadoop ecosystem tools (e.g., Hive, HDFS, Oozie, Airflow, Spark, Presto) Familiarity with streaming technologies such as Kafka or Samza Expertise in performance optimization, query tuning, and resource-efficient data processing Strong problem-solving skills and a track record of owning systems from design to production

About The Role The candidate must possess knowledge relevant to the functional area, and act as a subject matter expert in providing advice in the area of expertise, and also focus on continuous improvement for maximum efficiency. It is vital to focus on the high standard of delivery excellence, provide top-notch service quality and develop successful long-term business partnerships with internal/external customers by identifying and fulfilling customer needs. He/she should be able to break down complex problems into logical and manageable parts in a systematic way, and generate and compare multiple options, and set priorities to resolve problems. The ideal candidate must be proactive, and go beyond expectations to achieve job results and create new opportunities. He/she must positively influence the team, motivate high performance, promote a friendly climate, give constructive feedback, provide development opportunities, and manage career aspirations of direct reports. Communication skills are key here, to explain organizational objectives, assignments, and the big picture to the team, and to articulate team vision and clear objectives. Senior Process Manager Roles and responsibilities: Understand the business model on why things are the way they are, ask relevant questions and get them clarified. Breakdown complex problems in small solvable components, to be able to identify problem areas in each component. Conduct cost/benefit analysis and feasibility studies for proposed projects to aid in decision-making. Facilitate the implementation of new or improved business processes and systems. Coordinate with business stakeholders to identify gaps in data, processes and suggest process improvements. Understand and follow the project roadmap, plan data availability and coordinate with the execution team to ensure a successful execution of projects. Prescribe suitable solutions with an understanding in limitations of toolsets and available data. Manage procurement of data from various sources and perform data audits. Fetch and analyze data from disparate sources and drive meaningful insights. Provide recommendations on the business rules for effective campaign targeting. Interpret analytical results and provide insights; present key findings and recommended next steps to clients. Develop tangible analytical projects; communicate project details to clients and internal delivery team via written documents and presentations, in forms of specifications, diagrams, and data/process models. Audit deliverables ensuring accuracy by critically examining the data and reports against requirements. Collaborate on regional/global analytic initiatives and localize inputs for country campaign practices. Actively work on audience targeting insights, optimize campaigns and improve comm governance. Technical and Functional Skills: Must Have BS/BA degree or equivalent professional experience required Degree. Minimum 7+ years of professional experience in advanced analytics for a Fortune 500-scale company or a prominent consulting organization. Experience inData Extraction tools, Advanced Excel, CRM Analytics, Campaign Marketing, and Analytics knowledge- Campaign Analytics. Strong in numerical and analytical skills. Strong in Advanced Excel (prior experience with Google sheets is an added plus) Strong analytical and storytelling skills; ability to derive relevant insights from large reports and piles of disparate data. Comfortable working autonomously with broad guidelines. Passion for data andanalytics for marketing and eagerness to learn. Excellent communications skills, both written and spoken; ability to explain complex technical concepts in plain English. Ability to manage multiple priorities and projects, aligning teams to project timelines and ensuring quality of deliverables. Work with business teams to identify business use cases and develop solutions to meet these needs using analytical approaches. Manage regular reporting and ad-hoc data extract from other departments. Knowledge on analyzing digital campaigns and the tools/technologies of performance marketing. Experience with Google sheet/Excel. Good To Have Hands-on experience in digital marketing and/or 1:1 marketing in any channel; expert level knowledge in database marketing and CRM. Working knowledge in data visualization tools (Tableau, QlikView, etc.). Working knowledge of analytical/statistical techniques. Experience in Hadoop environment- Hive, Presto is a plus. Experience in Python/R. Previous consulting experience is a definite plus.

About The Role The ideal candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The role enables to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Senior Process Manager Roles and responsibilities: Understand the business model on why things are the way they are, ask relevant questions and get them clarified. Breakdown complex problems in small solvable components, to be able to identify problem areas in each component. Conduct cost/benefit analysis and feasibility studies for proposed projects to aid in decision-making. Facilitate the implementation of new or improved business processes and systems. Coordinate with business stakeholders to identify gaps in data, processes and suggest process improvements. Understand and follow the project roadmap, plan data availability and coordinate with the execution team to ensure a successful execution of projects. Prescribe suitable solutions with an understanding in limitations of toolsets and available data. Manage procurement of data from various sources and perform data audits. Fetch and analyze data from disparate sources and drive meaningful insights. Provide recommendations on the business rules for effective campaign targeting. Interpret analytical results and provide insights; present key findings and recommended next steps to clients. Develop tangible analytical projects; communicate project details to clients and internal delivery team via written documents and presentations, in forms of specifications, diagrams, and data/process models. Audit deliverables ensuring accuracy by critically examining the data and reports against requirements. Collaborate on regional/global analytic initiatives and localize inputs for country campaign practices. Actively work on audience targeting insights, optimize campaigns and improve comm governance. Technical and Functional Skills: Must Have BS/BA degree or equivalent professional experience required Degree. Minimum 8-10 years of professional experience in advanced analytics for a Fortune 500-scale company or a prominent consulting organization. Experience inData Extraction tools, Advanced Excel, CRM Analytics, Campaign Marketing, and Analytics knowledge - Campaign Analytics. Strong in numerical and analytical skills. Strong in Advanced Excel (prior experience with Google sheets is an added plus) Strong analytical and storytelling skills; ability to derive relevant insights from large reports and piles of disparate data. Comfortable working autonomously with broad guidelines. Passion for data andanalytics for marketing and eagerness to learn. Excellent communications skills, both written and spoken; ability to explain complex technical concepts in plain English. Ability to manage multiple priorities and projects, aligning teams to project timelines and ensuring quality of deliverables. Work with business teams to identify business use cases and develop solutions to meet these needs using analytical approaches. Manage regular reporting and ad-hoc data extract from other departments. Knowledge on analyzing digital campaigns and the tools/technologies of performance marketing. Experience with Google sheet/Excel. Good To Have Hands-on experience in digital marketing and/or 1:1 marketing in any channel; expert level knowledge in database marketing and CRM. Working knowledge in data visualization tools (Tableau, QlikView, etc.). Working knowledge of analytical/statistical techniques. Experience in Hadoop environment- Hive, Presto is a plus. Experience in Python/R. Previous consulting experience is a definite plus.

About The Role The ideal candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The role enables to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Senior Process Manager Roles and responsibilities: Understand the business model on why things are the way they are, ask relevant questions and get them clarified. Breakdown complex problems in small solvable components, to be able to identify problem areas in each component. Conduct cost/benefit analysis and feasibility studies for proposed projects to aid in decision-making. Facilitate the implementation of new or improved business processes and systems. Coordinate with business stakeholders to identify gaps in data, processes and suggest process improvements. Understand and follow the project roadmap, plan data availability and coordinate with the execution team to ensure a successful execution of projects. Prescribe suitable solutions with an understanding in limitations of toolsets and available data. Manage procurement of data from various sources and perform data audits. Fetch and analyze data from disparate sources and drive meaningful insights. Provide recommendations on the business rules for effective campaign targeting. Interpret analytical results and provide insights; present key findings and recommended next steps to clients. Develop tangible analytical projects; communicate project details to clients and internal delivery team via written documents and presentations, in forms of specifications, diagrams, and data/process models. Audit deliverables ensuring accuracy by critically examining the data and reports against requirements. Collaborate on regional/global analytic initiatives and localize inputs for country campaign practices. Actively work on audience targeting insights, optimize campaigns and improve comm governance. Technical and Functional Skills: Must Have BS/BA degree or equivalent professional experience required Degree. Minimum 8-10 years of professional experience in advanced analytics for a Fortune 500-scale company or a prominent consulting organization . Experience in Data Extraction tools, A dvanced Excel, CRM Analytics, Campaign Marketing, and Analytics knowledge - Campaign Analytics . Strong in numerical and analytical skills. Strong in Advanced Excel (prior experience with Google sheets is an added plus) Strong analytical and storytelling skills; ability to derive relevant insights from large reports and piles of disparate data. Comfortable working autonomously with broad guidelines. Passion for data andanalytics for marketing and eagerness to learn. Excellent communications skills, both written and spoken; ability to explain complex technical concepts in plain English. Ability to manage multiple priorities and projects, aligning teams to project timelines and ensuring quality of deliverables. Work with business teams to identify business use cases and develop solutions to meet these needs using analytical approaches. Manage regular reporting and ad-hoc data extract from other departments. Knowledge on analyzing digital campaigns and the tools/technologies of performance marketing. Experience with Google sheet/Excel. Good To Have Hands-on experience in digital marketing and/or 1:1 marketing in any channel; expert level knowledge in database marketing and CRM. Working knowledge in data visualization tools (Tableau, QlikView, etc.). Working knowledge of analytical/statistical techniques. Experience in Hadoop environment- Hive, Presto is a plus. Experience in Python/R. Previous consulting experience is a definite plus.