Top Data Engineer Jobs in Bangalore

Lead Data Engineer to design, build, and maintain scalable ETL pipelines and cloud data platforms, optimize data models/warehouses, ensure data quality and governance, and collaborate with analytics and business teams.

Senior technical leader responsible for designing, building, and scaling cloud-native data platforms and pipelines. Partners with stakeholders, mentors engineers, enforces engineering best practices, ensures data modeling, governance, and quality, debugs production issues, and contributes to architecture, design, and Agile delivery to support business outcomes.

Design, build and operate production ETL/ELT data pipelines in Python and FastAPI, maintain Spark/Scala workloads, ensure data quality, lineage and observability, collaborate with product and AI teams to deliver AI-ready data products, and apply testing, CI/CD and schema management.

Lead the design and implementation of scalable data platforms using Snowflake, while mentoring engineers, optimizing performance, and ensuring data governance compliance.

Design, develop, and maintain integration solutions ensuring data accuracy and security, while leading junior engineers and optimizing processes.

As a Senior Engineer for Strategic Data Solutions, you will manage data warehousing, reporting, and analytics for internal operations and external partners. Responsibilities include collaborating with business units, providing insights, and ensuring high-quality data reporting.

The role involves developing ETL pipelines, data integrations, and ensuring data quality, reliability, and compliance in risk analytics at State Street.

The Staff Data Engineer will lead data engineering initiatives, creating scalable data solutions, guiding teams, and maintaining data quality while utilizing various technologies.

Lead a team of engineers to build API-first, modular data tooling for Consumer Product & Innovation. Design data models, ETL and streaming pipelines, implement Databricks/Snowflake/AWS solutions, build APIs and dashboards, guide architecture, CI/CD and DevOps, and mentor engineers.

The Snowflake Senior Data Engineer will lead projects in data engineering, utilizing Snowflake and various AWS services to optimize data workflows and storage, while also guiding the team and collaborating with stakeholders.

The Lead Data Engineer will design and develop scalable data pipelines, lead system integration, mentor the team, and ensure data quality for analytics solutions.

The Senior Data Engineer will lead the data engineering strategy, focusing on building ETL pipelines, managing data warehouses, and ensuring data quality and availability.

As a Data Engineer, you will design and maintain data pipelines, enhance blockchain reporting, and ensure data quality while integrating external data sources and working with various teams.

Develop and maintain ETL pipelines and big data solutions on AWS and on-premises for consumption by data warehouses, marts, and BI. Use Python, SQL, Hadoop/Spark and RDBMS technologies; apply dimensional modeling and SDLC/Agile practices. Collaborate on best practices, troubleshoot data application issues, and support strategic initiatives and process automation.

Design and scale a Customer Data Platform to unify customer data, ensure data quality and governance, and support real-time personalization and analytics. Architect and implement ingestion pipelines, storage, distributed query engines, ETL/ELT workflows, and integrations while ensuring reliability, observability, and cross-functional collaboration.

Design, build, and maintain scalable data platforms and pipelines across AWS and Azure, supporting analytics, AI/ML, and business intelligence use cases. Collaborate with stakeholders and optimize data solutions for performance and cost.

Own and run conference scraping pipelines and expand coverage; deliver one-off and recurring automation/data projects using web scrapers and databases; maintain CMS; communicate with stakeholders; support ad hoc reporting and AI-driven data extraction projects; build integrations to streamline analyst workflows.

Build and maintain high-performance ETL/ELT pipelines and analytics-ready data warehouses using Python, Pandas (and Polars). Optimize for speed, memory, and parallelism; write complex SQL/PLSQL queries including window functions; perform validation, monitoring, debugging and production support; document workflows and collaborate with cross-functional teams.

As a Senior Data Engineer, you will design and manage real-time and batch data pipelines, collaborating with various teams to enhance data analytics capabilities.

The Lead Data Engineer will oversee data engineering responsibilities using AWS technologies and manage data workflows and architectures.

Design and build scalable cloud-native data platforms and lakehouse architectures. Develop and optimize batch and real-time ETL/ELT pipelines, ensure data quality and governance, enable CI/CD and automation, manage Databricks/Snowflake/Fabric platforms, and collaborate with BI and business teams.

Posting contains company overview but does not include any role responsibilities, tasks, or required qualifications for the Senior Engineer - Data position.

As a Senior Data Engineer, you'll design and improve data pipelines, ensure data quality, and collaborate with stakeholders to maximize data usage for analytics and operational needs.

As a Tech Lead, you will govern data modeling and analytics performance, support engineering teams, ensure scalable integration, and maintain standards for the lakehouse architecture.

Design, develop, and operate data pipelines in Azure Databricks, ensure data quality for HR, Purchasing, and Finance, and implement robust data models and validations.