Top Data Engineer Jobs in Chennai

We are looking for a Data Engineer with skills in Python, SQL, and Azure technologies to develop Big Data applications. Responsibilities include working with Spark and Docker to handle large scale data processing and analytics.

The Data Engineer role involves analyzing raw data, building data systems, conducting complex analyses, and enhancing data quality by collaborating with data scientists and architects.

This role involves collaborating with users to build data solutions, managing AWS data technologies, and automating workflows for efficiency.

The Azure Data Engineer will implement big data pipelines using Azure technologies, collaborate with stakeholders, and utilize tools like Data Factory and Databricks.

Design, build, and maintain scalable batch and streaming ETL/ELT pipelines, production data services (REST/gRPC), and cloud-based data infrastructure. Implement CDC and time-travel data architectures, ensure data quality with tests and CI/CD, optimize data models for OLTP/OLAP, and collaborate cross-functionally to deliver reliable production data systems.

As an Azure Data Engineer, you will innovate and maintain data engineering services for Fortune clients, develop software for large projects, and utilize Azure components for solutions.

Responsible for designing and developing a GCP data ecosystem, creating data pipelines, optimizing data architectures, troubleshooting issues, and mentoring junior engineers.

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

The Data Engineer will create and maintain data pipelines, optimize data delivery, build analytics tools, and support cross-functional teams with data infrastructure needs.

Principal Data Engineer responsible for building big-data solutions using PySpark and Databricks, writing and optimizing SQL, developing Python pipelines, and working with Hadoop/Hive, Git, Airflow/Dagster, and Azure.

Design, build, and maintain ETL data pipelines using Talend and Snowflake. Extract data from APIs, reverse-engineer Alteryx workflows, apply Data Vault modeling, implement CI/CD and AWS data services, document designs, and collaborate with architects, SMEs, and developers to deliver robust cloud-based data warehousing solutions.

Design, develop, and optimize AWS Glue ETL pipelines integrating data from S3, RDS, Redshift, and other AWS services. Transform data into analytics-ready formats, ensure data quality and security, tune performance, orchestrate workflows (Step Functions/Airflow), monitor jobs, and collaborate with analysts and stakeholders to deliver scalable data lake and warehouse solutions.

Design and deliver scalable, highly available data architectures and pipelines (batch and streaming). Lead technical delivery, mentor teams, manage client engagements, ensure security/compliance, and drive implementation using cloud (AWS/Azure/GCP), ETL, data lake/warehouse, and best SDLC/Agile practices.

Design and develop data solutions using Power BI and Snowflake. Perform data mining, feature engineering, time-series and IoT analytics, build predictive models and automated anomaly detection, maintain data pipelines and quality, and collaborate in an agile team to deliver analytics integrated into product systems.

The Data Engineer role involves data management, system design, and collaboration with teams to implement effective data solutions.

As a Data Engineer, you will develop and manage data pipelines, ensuring reliable data ingestion and delivery while optimizing for simplicity and performance.

The role involves designing scalable data pipelines and architectures using Microsoft Fabric, client engagement for requirements gathering, and optimizing data solutions for analytics and reporting.

As a Data Engineer, you will design, develop, and maintain data integration solutions, optimize ETL/ELT pipelines, and support data workflows for analytics and reporting.

Design, build, and maintain scalable ETL/ELT and real-time data pipelines on AWS. Manage Airflow DAGs, Kafka ingestion, Redshift optimization, data quality checks, API integrations, and cost optimization while collaborating with BI for reporting needs.

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, build, and maintain production data pipelines and integrations across applications, databases, and cloud services. Support data architecture, ingestion, embedding workflows for AI, data quality, monitoring, and platform reliability. Collaborate with Full Stack and AI teams to deploy scalable cloud-based data infrastructure and establish data engineering standards and best practices.

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

Design, develop and maintain data ingestion and transformation pipelines, optimize data architectures, manage data sources, and collaborate with teams on data analytics and ML datasets.

Lead the design and development of data pipelines and architectures, ensuring data quality and governance while mentoring junior engineers.

Configure and administer Collibra for data governance, integrate with enterprise systems, support data traceability, and enhance data quality.