Top Data Engineer Jobs in Bangalore

Lead the design and implementation of data pipelines and data architectures using AWS services. Oversee data engineering projects and collaborate with teams to optimize data processes.

Lead Data Engineer responsible for advanced AWS Data Engineering focusing on various tools and technologies, including Athena, Spark, DynamoDB, and more.

The Principal Data Software Engineer will design and optimize a cloud-native data platform for AI and analytics, ensuring compliance and security in healthcare data processing. Responsibilities include architecting scalable data architectures, developing data pipelines, collaborating with teams, and mentoring engineers.

The role involves designing and building data engineering solutions, developing data pipelines, ensuring data quality, and collaborating with teams to enhance data accessibility and decision making.

Responsible for designing and implementing data engineering processes, developing ETL solutions, managing metadata structures, and performing data profiling and analysis for data-driven outcomes.

The Senior Data Engineer will develop high-quality data solutions, maintain data models, and support analytics, collaborating closely with stakeholders and data teams.

The Senior Data Engineer role involves data mapping, ETL process development, and collaboration with stakeholders to deliver high-quality data solutions.

Design, implement, and maintain data ingestion pipelines; ensure data quality and compliance; collaborate with teams for structured data integration.

As a Tech Lead, you will govern data modeling and analytics performance, support engineering teams, ensure scalable integration, and maintain standards for the lakehouse architecture.

Design, develop, and operate data pipelines in Azure Databricks, ensure data quality for HR, Purchasing, and Finance, and implement robust data models and validations.

Design and maintain data ingestion pipelines, establish data quality frameworks, integrate various data sources, and collaborate with cross-functional teams.

The IT engineer will design and develop data pipelines in Azure Databricks, ensuring data availability and quality for Manufacturing & Engineering. Responsibilities include collaborative development, implementing complex data models, and applying software engineering practices.

The IT Engineer Tech Lead will govern data acquisition architecture, establish reusable interfaces, define standards, and support data engineering teams across multiple sources, ensuring quality integration and analytics.

The IT engineer will design and develop scalable data pipelines in Azure Databricks, ensuring data quality and availability for HR, Purchasing, and Finance. Key tasks include implementing ingestion from various sources, developing modular code, and collaborating across teams to refine user stories and align with governance standards.

Design and implement data ingestion pipelines, maintain metadata-driven services, ensure data quality and compliance, and collaborate with IT and business teams.

The IT engineer will design and develop data pipelines in Azure Databricks, ensuring data quality for Sales & Finance. Responsibilities include implementing data architectures, collaborating with stakeholders, and applying agile methodologies.

Design and optimize ETL/ELT pipelines using Azure technologies, develop complex SQL solutions, and streamline data lifecycle automation while ensuring production reliability and compliance.

The Senior Data Analytics Engineer at MariaDB designs and builds data pipelines, writes SQL queries, develops internal tools, and translates data into actionable insights. They will collaborate closely with stakeholders and leverage AI tools to enhance analytics workflows.

Design, build, and optimize scalable data solutions on Azure. Manage data pipelines and ensure data quality while collaborating with stakeholders.

The Lead Data Engineer will architect and optimize business intelligence solutions, develop data pipelines, manage SQL queries, and lead BI development using Power BI and Azure technologies.

Design, develop, and maintain ETL workflows and SQL-based data pipelines using SSIS, Denodo, SQL Server, and Oracle. Implement job scheduling with Control-M, perform data profiling and validation, optimize queries, support database operations, and assist with unit testing and data quality checks.

The job involves designing and maintaining data pipelines, building data models, creating dashboards for IT performance insights, collaborating with stakeholders, ensuring data quality, and keeping up with new technologies.

The Data Science Engineer III will develop and maintain scalable data pipelines, enhance data processing systems, and enable AI/ML use cases, collaborating with cross-functional teams and ensuring data quality.

Design and implement scalable data pipelines using Databricks and Apache Spark. Optimize lakehouse architectures and ensure data quality and governance. Collaborate with stakeholders for effective data solutions.

The Senior Data Engineer will design and optimize ETL/ELT pipelines, manage data integration, perform data validation, and support reporting solutions using various technologies.