ESM- Senior Data Engineer

The Role

• ESM is responsible for developing and maintaining applications

• ESM Developer Chapter Area comprises a diverse group of 70+ developers and leads the department in defining software development practices and growing developer capability.

• We work globally to support over 15 agile squads, delivering products and expertise to the entire

• Technology division composed of over 10,000 developers and production support engineers.

• In Enterprise Systems Management, we are not just building technology, we are shaping the future of banking.

• With hundreds of employees located around the world, we are an inclusive and international team representing a wide range of teams, roles, and cultures.

Your responsibilities:

 ESM is responsible for developing and maintaining applications in the following areas

 Data Management: asset and configuration management.

 Service management: automation, orchestration

 self-service portals, problem/incident/change management, and capacity management.

 Event Management: monitoring, log-collection at firmwide scales, event correlation, and analysis. Visualization: analytics & user interfaces.

 Application Performance Management: tracing and performance monitoring across huge distributed systems

 Collaborating with cross-functional teams to understand data requirements, and design efficient, scalable, and reliable ETL processes using Python and DataBricks

 Developing and deploying ETL jobs that extract data from various sources, transforming it to meet business needs.

 Taking ownership of the end-to-end engineering lifecycle, including data extraction, cleansing, transformation, and loading, ensuring accuracy and consistency.

 Creating and managing data pipelines, ensuring proper error handling

Essential skills/knowledge/experience:

 Experience- 6 -8 years

 ESM knowledge - Developing and maintaining applications

 Experience Python and Data Bricks

Desirable skills/knowledge/experience:

 Taking ownership of the end-to-end engineering lifecycle, including data extraction, cleansing, transformation, and loading, ensuring accuracy and consistency

 Creating and manage data pipelines, ensuring proper error handling,