Top Data Engineer Jobs in Bengaluru

As a Data Engineer, you will design and build reporting platforms, develop data pipelines, and work with various data technologies in a collaborative engineering team.

Design, develop, and maintain scalable data pipelines and platforms using Microsoft Fabric and Azure, implementing ETL solutions and managing data integration.

You will own critical data pipelines, design data models, build ingestion pipelines, ensure data correctness, collaborate with teams, and improve metrics.

Design, build, and maintain scalable data pipelines and infrastructure while optimizing data systems. Collaborate with teams to ensure data reliability and compliance, and document internal standards.

This role involves developing and optimizing data solutions using PySpark and Informatica BDM while collaborating with various teams on Risk & Compliance platforms.

As a Data Engineer, you'll optimize data workflows, design robust data solutions, and collaborate with teams to support data-driven initiatives.

The Data Engineer will build scalable data pipelines, perform data analysis and ensure high-quality data solutions aligned with enterprise data models.

The Data Engineer collaborates with Group Risk to create and support data pipelines for IFRS9 reporting, utilizing PySpark and Informatica BDM, ensuring data quality, and overseeing ETL processes.

Looking for a Data Engineer to build scalable data pipelines with PySpark, perform impact analysis, and ensure data quality in collaboration with the Group Operations Team.

The AWS Data Engineer will design and implement data pipelines using AWS services, develop ETL processes, and optimize data storage solutions.

Design, implement, and maintain data pipelines using Elasticsearch and data warehousing solutions, integrate data sources, and ensure data accuracy while collaborating with cross-functional teams.

The Data Engineer / Analytics Engineer will build scalable data models and pipelines using dbt and Snowflake while collaborating with stakeholders and engineers.

Zinier seeks a hands-on Senior Data Engineer to design and build a medallion data architecture on AWS, focusing on data governance, ETL pipelines, and AI/ML readiness while collaborating across teams.

The Data & Analytics Engineer designs, builds, and optimizes scalable data models in Snowflake using dbt, ensuring data integrity and high performance while collaborating with business units to translate requirements into technical specifications.

Design, build, and maintain scalable batch and real-time data pipelines on Azure using Kafka, Spark, Databricks and ADF. Optimize Snowflake models and SQL, process structured and semi-structured data, ensure data quality, performance, and collaborate with cross-functional teams.

Design, build, and optimize scalable ELT/ETL pipelines on Azure using ADF and Databricks, integrate data into Snowflake, implement Data Vault 2.0 modelling, ensure data quality and performance, and collaborate with stakeholders and analytics teams to maintain production workflows.

The role involves architecting data applications, optimizing systems for customer insights, and collaborating across teams to enhance video analytics for high-value clients.

The Senior Data Engineer will design and build scalable data platforms and pipelines, utilizing cloud technologies and leading data engineering practices. Responsibilities include maintaining ETL/ELT pipelines, collaborating with stakeholders, and ensuring data quality.

The Senior Data Engineer will design and optimize scalable data pipelines, implement real-time streaming pipelines, collaborate with data scientists, and oversee CI/CD and data quality practices.

The Senior Data Engineer will build and optimize data pipelines in Azure Databricks, migrate existing pipelines from Azure Synapse, and design scalable data models to support a financial services client's data platform modernization.

As a Data Engineer, you'll build and monitor large-scale data pipelines, develop the DBT setup for data transformation and solve customer problems using your SQL skills.

Develop and scale data management systems for AutoML and forecasting platforms, ensuring data reliability and implementing SLAs across pipelines.