Top Data Engineer Jobs in Bangalore

The Senior Azure Data Engineer will design, develop, and maintain data infrastructure and pipelines, ensuring data quality, integrity, and alignment with business objectives. Responsibilities include collaborating with teams and establishing best practices for data engineering.

Support design and blueprinting of the data platform, collaborating with Integration and Data Architects. Contribute to data architecture, integration, documentation, and provide solutions. Use Databricks for ETL, data modeling, cloud data services, governance, and large-dataset analysis while developing SME-level expertise.

The Data Engineer will translate analytical requirements into scalable data products, handle data modeling in Snowflake using dbt, manage data pipelines with Airflow, ensure data quality, and collaborate with cross-functional teams.

Design, build, and scale end-to-end data applications in Palantir Foundry: ingest external data, implement production-grade pipelines in Python/SQL, model ontologies, and deliver user-facing Workshop/React tools while establishing platform best practices.

Design, build, and maintain production-scale Amazon QuickSight dashboards. Implement SPICE optimization, Direct Query, data blending, and row-level security. Develop data models and complex SQL queries, validate KPIs, test dashboards, document designs and test cases, and communicate requirements and outcomes to business stakeholders.

The role involves designing data pipelines, developing and maintaining ETL processes, and collaborating with teams to implement data governance in a cloud environment.

Design, build, and operate production-grade, metadata-driven data ingestion pipelines and platform components. Implement CDC/delta/event patterns, integrate sources (SAP, Salesforce, SharePoint), manage metadata and data catalog (Unity Catalog), enforce data quality frameworks, and collaborate with cybersecurity, infrastructure, and business stakeholders in a CI/CD-driven environment.

Design, build, and modernize scalable GCP data pipelines integrating Adobe clickstream, Salesforce, POS, and CDPs. Implement Dataform/BigQuery ELT, semantic models, and governed AI-ready datasets to support analytics, self-service reporting, and Gemini-powered GenAI initiatives. Collaborate with analytics and business stakeholders on KPIs, metadata, and deployment best practices.

The Data Engineer will develop scalable data pipelines on Google Cloud, support analytics and AI projects, and ensure data quality and governance.

Design, build, and maintain scalable GCP data pipelines integrating Adobe clickstream with Salesforce, POS, and CDPs using Dataform and BigQuery. Develop semantic data models, governed analytics datasets, and AI-ready data structures to support enterprise reporting, self-service analytics, and Gemini-powered GenAI initiatives. Collaborate with stakeholders on KPIs, metadata, testing, deployment, and documentation.

The Senior Data Engineer at WPP Media will work with AI-driven media solutions, focusing on data integration and optimization to enhance client media investments and experiences.

The Data Management Engineer manages and optimizes the big data analytics environment, ensuring performance, reliability, and overseeing tools for the Analytics team. Responsibilities include support for AWS EC2 and AI integration.

The Data Quality Developer is responsible for enhancing applications, performing data quality checks, generating reports, and collaborating with stakeholders to ensure data governance and quality standards are met.

Design, build, and maintain large-scale data pipelines and ETL workflows using Apache Spark and Airflow. Optimize data storage and queries, monitor and troubleshoot production systems, write maintainable code, collaborate with cross-functional teams, mentor junior engineers, and apply responsible AI-assisted practices and semantic search over metadata.

The Senior Data Insights Engineer will build scalable data models, conduct in-depth analysis and visualization, and improve data quality for healthcare analytics. Responsibilities include partnering with various teams, applying AI in workflows, and designing dashboards for stakeholders.

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.

The Software Engineer will create and manage enterprise data architecture, guide data offices, ensure data quality, and promote data asset reuse.

The Software Engineer will create and integrate data architecture models, ensuring data quality and enabling stakeholder collaboration for a federated data strategy within Airbus India.

As a Data Architect, you will develop and integrate the enterprise data architecture, guide stakeholders, and promote data asset reuse while ensuring data integrity and quality assurance.

Design, build, and maintain scalable data integration pipelines and platform infrastructure using Snowflake, Airflow, Starburst, dbt, Kafka, and Fivetran. Ensure data integrity, performance, security, and collaborate with cross-functional teams to deliver high-quality data solutions and analytics support.

Develop, test, and implement data engineering solutions. Analyze datasets, build ETL jobs, and manage data structures for analytics.

The role focuses on designing and operating analytics pipelines on Google Cloud, utilizing tools like Apache Airflow and BigQuery, while implementing CI/CD practices.

Seeking a PLM Data Analyst to analyze and transform data from PLM systems, develop dashboards and data insights, and improve processes. Requires collaboration with engineering and IT teams.

The Senior Data Engineer will design and build data infrastructure and pipelines, enhance AI capabilities, and collaborate with teams on data solutions while mentoring junior engineers.

As a Senior Data Engineer, you will design and implement scalable ETL/ELT frameworks, lead data engineering projects, and mentor a team while ensuring operational stability of data pipelines.