Top Data Engineer Jobs in Chennai

Build, test, and maintain GCP-based data pipelines and ETL/ELT processes using Python and SQL. Optimize BigQuery queries, design data models, troubleshoot data quality and pipeline issues, collaborate with analysts and engineers, document solutions, and support project tasks while learning new tools.

Responsible for developing and configuring SAP Analytics Cloud tools, delivering effective planning solutions, and leading requirement gathering sessions. The role involves architecting solutions, collaborating with teams, and ensuring process improvement.

The Data Engineer will design, develop, and maintain ETL/ELT data pipelines, leveraging PySpark and Databricks to process large datasets, ensuring data quality, reliability, and performance optimization.

The role involves developing and maintaining data pipelines, optimizing workflows, managing cloud storage, and ensuring compliance with data security standards.

Develop and maintain scalable data pipelines, optimize workflows, manage cloud storage, ensure data security, and collaborate across teams.

Design, build, and optimize large-scale cloud data platforms and ETL/ELT pipelines on Azure. Implement data lakes, Delta Lake, Synapse, and Databricks solutions for batch and real-time processing, ensure data quality/governance, optimize SQL and analytics workloads, support CI/CD and deployments, and collaborate with stakeholders to deliver scalable data architectures and reporting.

Design and develop ETL pipelines, optimize data architecture, collaborate with data scientists to prepare data, and validate data quality.

This role involves establishing and implementing application systems, focusing on database analysis, programming, and significant experience with Oracle PL/SQL and data modeling techniques.

Serve as data steward and subject-matter expert for a mobile banking platform. Design and guide implementation of data collection, storage, retrieval, message content/metadata, and data-management best practices. Maintain and improve data quality, guide report development, and provide data-driven insights on customers, usage, and performance.

Design, develop, and implement advanced statistical and machine learning algorithms. Analyze disparate data sources to discover insights, build predictive models, prototype solutions, and collaborate with engineers to productionize models. Communicate findings to business and IT stakeholders and define system and functional requirements.

The FDC Data Engineer will implement an FDC framework in semiconductor manufacturing, focusing on process monitoring, data extraction, and collaboration with engineering teams.

The Data Engineer will design and maintain data pipelines, support AI use cases, and collaborate with data teams to improve data quality and accessibility.

The Azure Data Engineer will design, develop, and maintain data infrastructure and pipelines, ensuring data quality and collaborating across teams to prioritize data needs.

The role involves managing data pipelines in cybersecurity, collaborating with teams to implement solutions, and troubleshooting issues efficiently using Python and SQL.

The Lead Data Engineer will oversee enterprise data engineering services, focusing on data pipeline management, technical strategy, governance, and operational excellence across various data platforms and tools.

Lead Data Engineer is responsible for overseeing enterprise data engineering services, managing data pipelines, ensuring operational excellence, and providing technical leadership in data quality and governance across various platforms including Snowflake and Power BI.

Design and build scalable data pipelines, ETL, streaming ingestion and transformations. Collaborate with stakeholders to model data, automate quality testing, reduce platform costs, and embed new data techniques across the organisation while ensuring security and operational controls.

As a Data Engineer, you will innovate and maintain technology services, develop software systems for large projects, and work across all SDLC phases.

Lead the data team to build scalable data products, create data pipelines, partner with business teams, and ensure data quality while impacting revenue and decision-making.

Design, implement, and maintain data pipelines using Elasticsearch and data warehousing solutions, integrate data sources, and ensure data accuracy while collaborating with cross-functional teams.

This role involves building and implementing application systems, conducting feasibility studies, and providing operational support while also guiding junior analysts and ensuring compliance with standards.

The Data Engineer will design and maintain data models, develop BI solutions, integrate data, and optimize data flows while collaborating with stakeholders.

As a Data Engineer, you will build scalable ETL/ELT pipelines, optimize data structures, and develop impactful Power BI solutions for stakeholders.

The role involves designing and building data systems using various technologies, especially within Microsoft Azure, and requires experience in system integration and data warehousing.

Design, build, and operate data flows and ETL pipelines for ML; manage data versioning, CI/CD, dependency management (poetry); deploy scripts/models; use orchestrators and GCP data services.