Top Data Engineer Jobs in Bangalore

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, build, and optimize telematic data pipelines and architectures using SQL and AWS. Assemble large datasets, automate processes, support analytics and cross-functional teams, and improve data delivery, scalability, and operational insights.

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.

Lead technical direction for data platform capabilities: design and maintain data pipelines, reporting models, and data governance to support trusted metrics and AI/LLM agentic workflows. Drive architectural improvements, mentor engineers, collaborate on roadmaps, and represent technical capabilities externally.

Design, build, and maintain Databricks-based data pipelines using PySpark and Delta Live Tables. Implement data models, optimize complex SQL and PySpark transformations, manage Unity Catalog for governance, support AI/ML downstream consumption, monitor and troubleshoot pipelines, contribute to CI/CD, and help power the semantic layer for Power BI dashboards.

Design, build, and maintain cloud data pipelines and architectures using SQL, Python, Snowflake, and AWS. Implement CI/CD for data workflows, use developer assistance tools, and collaborate across teams to deliver reliable data solutions.

Design, build, and maintain scalable ELT/data pipelines and connectors using Airflow, Python, and PySpark. Implement DataOps and CI/CD for data workflows, monitor and troubleshoot pipelines, validate data quality, collaborate with cross-functional teams, and document data processes and governance.

Design, build and maintain ETL mappings and data models; write SQL and Snowflake queries; manage ETL/infrastructure on AWS (EC2); use Informatica, Control-M and ServiceNow; script in Python/Shell/PowerShell; collaborate with onshore/offshore teams and define BI delivery strategy.

Design, build, and maintain cloud-based ETL/data pipelines in Snowflake. Extract and transform data from heterogeneous sources, optimize SQL performance, implement monitoring, and collaborate across teams. AWS and Python experience are advantageous.

Design, develop, and coordinate cloud data solutions using Snowflake, Python, and AWS. Support product releases, deployments, testing, and post-install support. Collaborate with architects and tech leads, troubleshoot issues, and maintain documentation. Contribute to agile squads, adopt new technologies, and enable Fidelity Wealth business data needs.

Lead database design, data modeling, migrations, and schema evolution across MySQL/Postgres and GCP databases. Design and operate config-driven ETL/ELT pipelines and streaming ingestion, enable CI/CD, troubleshoot data flows, and mentor offshore DB/ETL engineers.

Design, build, and maintain cloud data pipelines and streaming solutions using Java, Kafka, AWS services, SQL/warehouse technologies, and Python. Implement CI/CD, automated testing, and resilient microservice-based systems. Collaborate in a small agile team and ensure secure identity/authentication controls.

Design, build and optimize ETL pipelines and cloud data workflows using Python, PySpark, AWS Glue and Lambda. Implement data models and schemas in PL/SQL/PostgreSQL, integrate AWS services (SNS, Step Functions), and troubleshoot pipelines for performance, scalability and reliability.

Design, develop, and optimize PL/SQL artifacts and Python ETL scripts; tune SQL and Oracle performance; ensure data integrity and availability; integrate systems via APIs; support production deployments and monitoring; collaborate with engineers and analysts; administer Oracle and PostgreSQL; use GitLab and Jira for version control and tracking.

Develop and maintain data pipelines and applications using Python and Pandas, apply OOP and data structures, write and optimize SQL, and communicate with stakeholders. Familiarity with Agile, DevOps/CI-CD tools (Jenkins, Git, Jira), AWS, web frameworks (Django/Flask), and Snowflake is a plus.

Perform data migration/refresh from production, support Python-based data refresh framework, run post-migration fixes, validate and reconcile data, monitor and resolve batch jobs and pipeline issues, perform performance checks, and coordinate with dependent teams.

Design, build, and maintain ETL pipelines and frameworks on AWS. Deploy and troubleshoot containerized applications (Docker, EKS), support CI/CD and build tooling, work with SQL/Oracle and ORM tools, and use job schedulers like Autosys/Airflow. Collaborate in Agile/SCRUM environments.

Design, build, and maintain ELT/data pipelines and workflow orchestration using Airflow, Python, and PySpark. Develop custom connectors, implement DataOps and CI/CD for data, monitor and validate data flows, collaborate with cross-functional teams, and document data workflows and governance.

Design, develop, and optimize ELT/ETL pipelines and data models using SQL, Python, and cloud services (AWS). Enable cloud data movement to Snowflake, perform SQL performance tuning, support code migrations, and collaborate in agile, distributed teams to deliver analytics-ready data solutions.

Design, build and maintain data solutions using Oracle SQL/PLSQL and Informatica ETL. Develop backend and APIs with Java/Spring Boot, work with XML/JSON, web frameworks (Angular/React), and operate in Unix environments. Use cloud/container tooling (AWS, Kubernetes, Docker, Rancher), Splunk for logging, follow Agile, collaborate across distributed teams, and support migrations and CI/CD pipelines.

Join the Event Streaming and Data Replication platform as a Data Engineer to design, build, and operate cloud-native data platforms. Work with Airflow, Spark, Kubernetes, and Python; deploy containerized apps on AWS/Azure; use IaC (Terraform/CFT/ARM); implement CI/CD (GitHub, Artifactory, Jenkins); configure monitoring and alerts; and collaborate across teams to deliver highly available, scalable solutions.

Design, build, and maintain ELT/data pipelines and workflow orchestration using Airflow, Python, and PySpark. Develop custom connectors to ingest diverse data, implement DataOps and data CI/CD pipelines, monitor and troubleshoot pipelines, validate data quality, collaborate with cross-functional teams, document workflows, and work with large-scale distributed datasets and visualization tools.

Design, build, and maintain scalable data pipelines and ETL processes using Python and PySpark. Orchestrate workflows with Airflow, query data with Trino and Hive, and write efficient SQL. Collaborate in Agile/Scrum teams to deliver data solutions and optimize data platform performance.

Deliver data engineering and analysis work using Python, PySpark, SQL and data platforms (Airflow, Trino, Hive). Produce LLD, coordinate offshore teams, follow Agile/Scrum, and work with container platforms (Linux, OpenShift, Kubernetes) and visualization (Superset). Banking domain experience is a plus.

Design, develop, deploy, and administer SSIS-based ETL solutions and data pipelines. Optimize SSIS packages and SQL performance, support data warehouse modeling, monitor ETL operations, provide L2/L3 production support, enforce data quality and governance, and collaborate with BI teams for reporting and migrations across environments.