Top Data Engineer Jobs in Bangalore

The Senior Software Developer will develop and support Qlik Sense applications, ensure best practices, and improve analytics processes while collaborating with clients and teams.

Design, build, and operate scalable, reliable data pipelines and services (Go/Scala) to power internal data products. Partner with engineers, analysts, and product stakeholders to model datasets, improve data platform architecture, ensure data quality and observability, and support AI/LLM-enabled features. Lead design reviews, mentor teammates, and collaborate globally on ingestion, governance, and production operations.

Design, develop, and maintain data solutions and ETL pipelines on AWS BigData. Ensure data quality, monitor and troubleshoot pipelines, document workflows, collaborate with cross-functional teams, and mentor junior engineers to deliver scalable data processing and migration solutions.

Design, develop, and maintain data solutions; create data pipelines, ensure data quality, and implement ETL processes.

Design, develop and maintain scalable data pipelines and ETL processes. Ensure data quality, troubleshoot data issues, optimize pipeline performance, collaborate across teams, and mentor junior engineers.

Design, develop, and implement large-scale data engineering solutions on cloud (primarily Azure). Build ETL/streaming pipelines, manage data lakes, use Databricks and SQL for analytics, implement CI/CD, and provide development, administration, and support across data platforms.

Operate and automate scalable ETL/ELT pipelines, implement CI/CD and IaC for data assets, ensure data observability and quality, enforce security/compliance, and support data scientists and analysts to maintain highly available global data infrastructure.

Design, build, and optimize 2K's core data platform (Snowflake/Databricks, S3, Kafka/Kinesis). Enable self-service DaaS, scale streaming and Spark workloads, implement RBAC and interoperability (Iceberg), and provide technical leadership to ensure high-performance, secure, and cost-efficient distributed data systems.

Design, build, and automate end-to-end ETL/ELT pipelines and large-scale data processing (batch and streaming) on Azure and AWS. Manage data lakehouse storage, implement data modeling and quality checks, and deploy infrastructure and CI/CD for reliable, observable data platforms.

Design, build, and automate end-to-end ETL/ELT pipelines and large-scale data processing using Azure and AWS services, Databricks/EMR, streaming tools, and data lakehouse technologies. Implement data modeling, transformation (dbt), quality checks, infrastructure as code, and CI/CD while ensuring observability and containerized deployments.

Design, build, optimize, and support production-grade Snowflake/dbt data pipelines. Implement data quality frameworks, write production SQL and Python, enable AI integrations and adopt AI-native tooling to ensure reliable analytics at enterprise scale.

Design, build, optimize, and support production-grade Snowflake data pipelines and dbt models with robust quality checks. Implement SQL/Python transformations, pipeline automation, AI integration for LLM workflows, and adopt AI-native tooling to ensure reliable enterprise analytics for executive reporting.

Design, build, and maintain scalable Snowflake/dbt data pipelines and architectures for enterprise reporting. Implement production-grade SQL and Python transformations, pipeline automation, and data quality tests. Instrument pipelines for metric reliability and integrate AI/LLM outputs to support analytics and executive reporting.

Design, build, and operate enterprise-scale data pipelines and architectures using Snowflake and dbt. Produce production-grade SQL and Python ETL, implement data quality tests, and integrate AI/LLM outputs to enable reliable executive metrics and analytics.

Design, build, and maintain Power BI semantic models, reports, and dashboards supporting NPS, TAC analytics, and customer health. Develop Power Automate workflows, author advanced DAX, collaborate on Snowflake/dbt optimization, enable configurable dashboard hierarchies, and help evaluate Microsoft Fabric and AI-augmented BI features for executive reporting and automated insight delivery.

Design, build, and maintain scalable ELT/ETL pipelines into Snowflake, create analytics-ready dbt data models, optimize Snowflake performance, enforce data quality/lineage/governance, and partner with architects and stakeholders to deliver reliable, maintainable data solutions.

Develop and maintain scalable data processing platforms and pipelines, ensure data availability, participate in full SDLC, optimize and operate data integrations, collaborate with cross-functional teams, and support automation and enterprise AI integrations.

Design, develop, and maintain data solutions and ETL pipelines using AWS Glue and PySpark. Ensure data quality, optimize workflows, troubleshoot issues, collaborate with cross-functional teams, lead and mentor team members, and make technical decisions to deliver scalable cloud-based data architectures.

Lead design and implementation of Azure cloud Lakehouse and ETL/ELT solutions using Databricks and PySpark. Architect medallion Delta Lake platforms, build metadata/YAML-driven pipelines, optimize Spark workloads, implement CI/CD and IaC, enforce data governance and quality, mentor engineering teams, and drive cloud migration and stakeholder alignment for enterprise analytics and downstream applications.

Design and build scalable data platform capabilities using AWS, cloud warehouses, dbt, and Airflow. Automate end-to-end ELT pipelines, implement LLM-augmented features (RAG, semantic search), and drive AI-agentic workflows for data quality, self-service, and real-time ML use cases.

Lead design and implementation of data governance and data quality monitoring solutions for Fidelity Wealth. Translate business requirements into scalable data pipelines and platforms using cloud technologies. Collaborate with architects, SMEs, analysts and stakeholders to drive adoption, automate CI/CD, and improve data quality and observability to accelerate insights.

As a Data Engineer at NXP, you'll enhance the R&D data analytics platform, collaborating cross-functionally, designing ETL pipelines, ensuring data quality, and optimizing performance.

The IT Data Engineer II designs and optimizes data pipelines, develops ETL processes, enforces data governance, and collaborates with stakeholders on data solutions.

Design and maintain data pipelines and dashboards, optimize SQL queries, ensure data quality, and collaborate with stakeholders to support data-driven decisions.

The role involves leading the design and implementation of scalable data architecture and platforms, guiding teams in alignment with business objectives and driving data strategy and governance.