Associate Vice President - Senior Lead Data Engineer

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.

Your area of work:

Are you ready to work at the intersection of financial markets, cutting-edge technology, analytics, and business insight We're looking for a passionate Data Product Developer / Analytics Engineer to join our international team and partner closely with business stakeholders to build scalable, high performance analytical data products processing petabytes of sensitive data in near real time.

As part of StatistiX IT within the Clearing & Risk IT department, you'll contribute to a next-generation cloud native analytics platform that powers mission critical regulatory, risk, and statistical use cases. Built on data mesh principles, the platform enables domain-driven data ownership, interoperability, and agility, and serves as a foundation for advanced analytics, reporting, and AI/ML innovation.

In this role, you will work hands-on on the design, engineering, and implementation of analytics-ready data products on Databricks and Google Cloud Platform (GCP). You will play a key role in the migration of on-premise analytical workloads and Zeppelin-based solutions to modern cloud analytics architectures, ensuring continuity, performance, and improved usability for business users. From analytics design and semantic modeling to deployment and production support, your impact will be felt across the financial ecosystem, enabling better insights, transparency, and decision-making at scale.

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 analytical data products and transformation pipelines, delivering analytics, ready datasets aligned with business and regulatory needs.
• Apply a strong analytics background to enable data consumption through leading BI and analytics platforms such as Databricks, Power BI or Looker, including support for consistent KPIs and business metrics.
• Implement and optimize data integration and transformation solutions using Python, Spark, Kafka with a strong focus on analytical workloads.
• Collaborate closely with cross-functional and business teams to understand analytics requirements and translate them into trusted, reusable data products.
• Optimize and manage analytical data storage, modeling, and retrieval across GCP or Azure, and Cloudera-based platforms, ensuring performance and cost efficiency for analytics use cases.
• Ensure data quality, consistency, and integrity through rigorous validation, reconciliation, and analytical testing frameworks.
• Monitor and troubleshoot analytics pipelines and data products to ensure reliability, scalability, and stable production operations.
• Stay up to date with analytics engineering, cloud, and data platform trends to continuously improve analytical capabilities, data models, and consumption patterns.

Your profile:

• Education: University degree in Computer Science, Engineering, or a related technical field.
• Experience: Ideally 8+ years of relevant professional experience in data engineering or data product development.
• Cloud Expertise: Solid hands-on experience with hyperscalers such as Google Cloud Platform (GCP) or Microsoft Azure.
• Programming Skills: Proficient in languages such as Scala/Spark, Python/PySpark, and Java.
• Data Architecture: Strong understanding of data modeling, data warehousing, and data platform design.
• Workflow Orchestration: Experience with batch scheduling and workflow orchestration tools; familiarity with Control-M and Informatica is a plus.
• Database Knowledge: Solid working knowledge of SQL and relational databases.
• Version Control: Proficient with tools like Git, GitHub, or GitLab.
• DevOps & CI/CD: Exposure to CI/CD pipelines and DevOps methodologies is an advantage.
• Domain Knowledge: Good understanding of financial markets; knowledge of Trading, Clearing and Risk management functions is a big advantage.
• Communication: Strong interpersonal and communication skills to collaborate effectively across diverse teams.
• Languages: Fluency in English is required; German language skills are a plus.