Senior Associate - Senior Data Product Developer [T500-21046]

About Deutsche Börse Group:

Headquartered in Frankfurt, Germany, Deutsche Börse Group is a leading international exchange organization and market infrastructure provider. They empower investors, financial institutions, and companies by facilitating access to global capital markets.

Their India centre is located in Hyderabad, serves as a key strategic hub and comprises India’s top-tier tech talent. They focus on crafting advanced IT solutions that elevate market infrastructure and services. Deutsche Börse Group in India is composed of a team of capital market engineers forming the backbone of financial markets worldwide.

Area of work:

Are you ready to work at the intersection of financial markets, cutting-edge technology, and data innovation? We’re looking for a passionate Data Product Developer / Data Engineer to join our international team and help build scalable, high-performance applications that process petabytes of sensitive data in real-time.

As part of the StatistiX IT within the Clearing & Risk IT department, you’ll be contributing to a next-generation data platform that powers mission-critical regulatory use cases. Building on data mesh architecture, our platform enables domain-driven ownership, interoperability, and agility across the organization and serves as the foundation for AI/ML innovation.

You’ll work on designing, engineering and developing data products and applications that handle billions of datasets daily, ensuring reliability, accuracy, and compliance. From architecture to deployment and production support, your impact will be felt across the financial ecosystem.

If you're excited by the challenge of building intelligent, resilient data systems in a fast-paced, data-centric environment—we want to hear from you.

Your responsibilities:

• Design, develop, and maintain scalable data pipelines (ELT) and data products in offering batch and steaming.
• Implement data integration solutions using Python, Scala, Spark, Kafka and RDBMS such as Oracle.
• Collaborate with cross-functional teams to understand data requirements and deliver solutions.
• Optimize and manage data storage and retrieval processes on GCP, Azure, and Cloudera platforms.
• Ensure data quality and integrity through rigorous testing and validation.
• Monitor and troubleshoot data pipeline performance and reliability.
• Stay updated with the latest industry trends and technologies to continuously improve our data infrastructure

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