Top Data Engineer Jobs in Bangalore

As a Data Engineer, you'll optimize data pipelines and models using PySpark, SQL, and GCP. Responsibilities include processing large datasets and designing enterprise-scale data platforms.

Designs, builds, and operates scalable AWS-based batch and streaming data pipelines and platforms (Lakehouse and warehouse). Owns architecture, performance, security, and cost optimization; implements transformations (SQL/dbt, PySpark), Kafka ingestion, Airflow orchestration, and CI/CD/Terraform. Partners with product and platform teams, mentors engineers, and drives data modeling, schema evolution, and operational excellence.

Lead design and implementation of product-level data architecture and scalable ETL/ELT pipelines to support analytics and AI/ML. Define and maintain dimensional models, fact/dimension tables, and data quality monitoring. Partner with product, data science, and platform teams to produce analytics- and AI-ready datasets, drive architectural standards, and mentor data engineers.

Lead architecture and implementation of a scalable next-generation data platform. Design and build batch, streaming, and near-real-time data pipelines, data models, observability, lineage, and ELT/ETL processes. Drive technical vision, evaluate modern data technologies, optimize cost and performance, and mentor engineering teams while collaborating with data scientists, analysts, and product owners.

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

Design, build, and lead production data and ML pipelines (streaming and batch) using Python and PySpark. Develop ETL, feature engineering, EDA, data quality, and anomaly detection. Use Hadoop/Hive, Pandas, SQL/NoSQL, Airflow/Jenkins and CI/CD tooling. Write tested, maintainable code, collaborate with stakeholders, and mentor teams while communicating technical concepts to technical and non-technical audiences.

Lead development and support of Honeywell's Informatica Product 360 PIM/MDM: oversee inbound/outbound jobs, analyze and implement change requests, perform code migrations and upgrades, build PIM modules and data quality customizations, configure Power BI reports, guide downstream integration, run demos with stakeholders, and contribute to AI automation.

Design, build, and scale data pipelines for advertising systems, ensure data compliance, and develop platform tooling while collaborating globally.

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

The AWS Data Engineer will work on designing and building cloud-based solutions, utilizing AWS services, and integrating systems for clients. Requires experience with various AWS tools and Java development.

Build, optimize, and maintain scalable ETL/ELT data pipelines and workflows using Python, PySpark, SQL, and cloud services (GCP/AWS/Azure). Ensure data quality, performance tuning, observability, and collaborate with cross-functional teams to deliver governed data products and documentation.

Build and maintain scalable Azure and Databricks ETL/ELT pipelines using SQL and Python/PySpark. Design cloud-native data lakes, ingest/process data with ADF/ADLS, optimize data models, monitor pipeline health, troubleshoot failures, and collaborate with architects, QA, DevOps, and business teams.

Lead design and build scalable lakehouse architectures on Azure Databricks: implement Medallion patterns, Delta Lake tables, Unity Catalog governance, PySpark transformations, ADF pipeline orchestration, SQL optimization, CI/CD and performance tuning to deliver enterprise data marts and analytics-ready assets.

The role involves data modeling, troubleshooting complex issues, optimizing storage architectures and mentoring junior engineers while working with GCP and Python.

The Data Engineer will design, build, and maintain ETL pipelines and data products, utilizing big data technologies and ensuring efficient data architecture. Responsibilities include troubleshooting complex issues, developing scalable solutions, and managing databases and data security compliance.

Design, build, and operate Digital Data Platform pipelines and DataOps capabilities. Implement ETL/ELT, streaming, API integrations, data quality, governance, security, and self-service access using Python, SQL and GCP services. Collaborate with stakeholders to document requirements, test and troubleshoot data processes, and enable analytics and BI consumption.

The Senior Technical Consultant will manage complex data projects, build data pipelines, integrate systems, support deployments, and mentor junior staff.

The Lead Data Engineer will design, optimize cloud-based data pipelines, implement data models, ensure data quality, collaborate across teams, and build automated ETL/ELT workflows.

The Data Engineer III role involves designing and maintaining data pipelines, optimizing SQL queries, managing data workflows, and communicating with stakeholders. Responsibilities include leveraging cloud technologies and collaborating on reporting solutions while identifying opportunities for innovation.

Lead the design and development of scalable data architecture and ETL/ELT pipelines, ensuring AI readiness and high-performance analytics across products.

The Associate Data Engineer will assist in building and maintaining data pipelines, writing SQL queries, and ensuring data quality using tools like Snowflake and Matillion.

Responsible for designing and building data integration solutions, optimizing ETL processes, mentoring analysts, and managing data flow across systems.

The Data Engineer will design and implement data integration solutions using Azure technologies, develop ETL processes, and optimize data workflows while mentoring junior analysts.

Lead the maintenance and expansion of reporting platforms, develop data transformations in SQL, manage junior engineers, and ensure data quality on Google Cloud Platform.

As a Senior Analyst-Data Engineer, you will design, develop, and optimize data pipelines, ensure data quality and transform marketing data into insights.