Top Data Engineer Jobs in Bangalore

The Data Engineer will optimize the elluminate® platform for clinical data through coding, ETL processes, and deliver client-focused solutions while ensuring compliance with industry standards.

The Data Engineer is responsible for designing, implementing, and managing data infrastructure and analytical systems, mentoring junior engineers, and optimizing data processes using tools like Databricks and Azure.

As a Senior Data Engineer, you will lead data engineering initiatives, build data pipelines, resolve issues, and collaborate with teams to achieve strategic goals.

As a Senior Data Engineer, you will architect system migration to Oracle Cloud, integrate AI/ML solutions, and lead data quality initiatives.

The Data Quality Engineer ensures data reliability and integrity by designing systems for data validation, monitoring data pipelines, enforcing quality standards, and collaborating with teams for data-driven decisions.

The Senior Data Engineer is responsible for preparing data for analysis, supporting application teams, ensuring data quality, automating processes, and collaborating with various teams while presenting insights effectively.

The role involves building HR data solutions, utilizing Workday for reporting, and migrating data to Snowflake, while ensuring data privacy and quality.

The Senior Data Engineer designs and operates data products and pipelines on an AWS platform, optimizing for performance, security, and cost while mentoring engineers and driving technical standards.

Lead the design and evolution of enterprise data platforms, ensuring scalable and high-performance data solutions. Collaborate cross-functionally to deliver data-driven outcomes and mentor a team of engineers.

As a Data Engineer, you will design, develop, and maintain data solutions including creating efficient data pipelines and implementing ETL processes while ensuring data quality and integrity.

As a Data Engineer, you will design, develop, and maintain data solutions, create data pipelines, ensure data quality, and implement ETL processes.

Design and maintain data solutions, build ETL/ELT processes, ensure data quality, and optimize scalable data pipelines for large-scale processing.

As a Data Engineer, you will design, develop, and maintain data solutions, create data pipelines, ensure data quality, and implement ETL processes.

Design, develop, and maintain data solutions for data generation and processing. Create data pipelines, ensure data quality, and implement ETL processes.

As a Data Engineer, you will develop data-driven solutions, manage data pipelines, improve automation, and ensure data quality through ETL processes.

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

As a Data Engineer II, you'll design and maintain data pipelines, collaborate with cross-functional teams, and ensure data quality and compliance.

The Data Engineer will enhance Axi's data capabilities, develop ETL/ELT pipelines on Azure Databricks, ingest data, ensure quality, and collaborate with various teams.

The Data Engineer will design and develop efficient data patterns on AWS and on-premises, ensuring quality ETL processes, collaborating with teams, and troubleshooting issues.

Design and operationalize enterprise data solutions on GCP. Build data pipelines, analyze and re-platform data warehouses, and communicate complex technical topics. Requires extensive experience in big data tools, databases, and GCP services.

The Data Engineer designs and maintains data pipelines to support AI-driven healthcare applications, ensuring data integrity and compliance while optimizing infrastructure for analytics and machine learning.

The Data Engineer role requires expertise in DevOps and Data Engineering technologies, particularly in Kubernetes, Terraform, Azure, and building data pipelines. Responsibilities include provisioning data platforms, managing CI/CD pipelines, and implementing IaaS architecture.

Design, build, and operate high-scale batch and streaming data pipelines, aggregates, and dimensional models. Ensure data quality, observability, and performance; optimize costs; implement orchestration/CI-CD; and partner with backend, ML, and product teams to deliver analytics-ready datasets for prediction, BI, and measurement.

Design, build, and maintain scalable data pipelines using Python and SQL on cloud platforms, ensuring data quality and collaboration with analysts and teams.

The Principal Data Engineer will design and operate scalable data solutions, lead a data engineering team, ensure quality and security, and optimize data performance to support analytics and AI initiatives.