Top Data Engineer Jobs in Chennai

Lead the design and implementation of ETL processes, develop Python solutions, and create data visualizations, collaborating with cross-functional teams.

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.

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

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.

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 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.

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

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.

Design, build, and operate data pipelines and ETL workflows on GCP using BigQuery, Dataflow, Cloud Composer and Dataproc. Develop SQL-based analytics, implement data processing with Python/Java and PySpark, and apply Dataplex for data governance. Collaborate with teams to deliver scalable, production-ready data solutions.

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

Design and implement modern data warehouse solutions using Databricks and cloud (Azure/AWS). Develop, orchestrate (Airflow) and troubleshoot ETL pipelines (batch and streaming), build dimensional data models for reporting, collaborate with architects and business stakeholders, mentor team members, and drive technical discussions.

Design, build, and maintain scalable ELT pipelines in GCP ingesting data from REST/SOAP APIs and enterprise systems. Use Dataform, Airflow, Cloud Run/Functions, Workflows, Pub/Sub, and Terraform to deliver analytics-ready datasets, support Looker dashboards and ML models, build AI agents for automation, and provide production support during PST month-end close cycles.

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, build, and maintain scalable ETL/ELT data pipelines using Alteryx and SQL. Create and optimize data models and Power BI dashboards, ensure data quality and performance, automate reporting workflows, monitor production pipelines, and collaborate with stakeholders to deliver reliable business intelligence solutions.

Design and develop data-driven solutions and scalable data pipelines using Python and SQL. Leverage Azure data products to build robust, secure architectures, ensuring data integrity, performance, and governance while supporting data-centric client projects.

Design and develop scalable data-driven solutions and pipelines using Python and SQL. Leverage Azure data services to build secure, high-performance architectures, ensuring data integrity, governance, and overall success of data projects.

Design, build, and maintain scalable ETL/data pipelines and data management blueprints. Ingest, transform, and curate large complex datasets for analytics, support cloud (AWS) implementations, enable downstream consumers, and provide technical leadership and operational support to ensure data governance, quality, and automation.

Design and build scalable data pipelines and architectures on Azure using ADF, Databricks, and Synapse. Implement Kimball/Data Vault modeling, write ETL in Python and T-SQL, ensure data governance (Azure Purview), automate tests, troubleshoot issues, document processes, and collaborate across teams.

Hiring data professionals (Analyst, Engineer, Scientist) to extract, clean, model, and visualize data; build ETL/ELT pipelines, data lakes/warehouses; develop ML models; run A/B tests; provide insights via dashboards and cross-functional collaboration.

Manage and maintain catalog, product, CBOM/BOM, pricing, and configuration data across multiple systems. Translate specs into system inputs, support product introductions and change implementation, host validation calls, drive change management and documentation, ensure data quality and cross-functional alignment.

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.

As a hands-on data engineer, you'll build and enhance scalable data platforms, develop data pipelines, and collaborate with various teams to improve data solutions and system performance.

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.