Principal Data Engineer

Principal Data Engineer – Asset Management / Investment Management

Berlin – Hybrid | Base Salary: €120–150k + Bonus

AI Futures have been retained by a fast-growing, technology-driven investment firm managing over €2 Billion in assets. The firm is redefining equity research, portfolio construction, and investment decision-making through proprietary AI and data-driven platforms.

As Principal Data Engineer (m/f/d), you will take a leading role in designing and evolving the firm’s data and analytics ecosystem - ensuring scalable, high-performance infrastructure that underpins cutting-edge quantitative research and AI-driven investment strategies. This is a strategic and visible hire at the intersection of data engineering, AI, and finance, offering a rare opportunity to shape the data backbone of a next-generation asset manager.

The Role

• Lead the design and evolution of modern data architectures and ETL/ELT pipelines to support large-scale, complex financial datasets.
• Architect and optimize data lakehouse and cloud-native solutions across AWS, Snowflake, and Databricks.
• Partner with quantitative researchers, data scientists, and investment analysts to translate financial and research needs into robust, production-grade data systems.
• Drive the integration of AI/LLM workflows, including document intelligence, retrieval-augmented generation (RAG), and model-driven analytics for unstructured financial data.
• Define best practices in data governance, quality, lineage, and observability, ensuring data reliability across research and trading workflows.
• Provide technical leadership and mentorship across the data engineering function, influencing architectural decisions and long-term data strategy.

Candidate Profile

Extensive experience as a senior or principal-level data engineer in financial services - ideally within asset management, investment management, or quantitative research environments.
Deep expertise in Python (Pandas, NumPy, FastAPI) and SQL, with a proven record of building and maintaining complex data pipelines (Airflow).
Strong proficiency in Snowflake, Databricks, Delta Lake, and AWS-based data infrastructure.
Experience with DevOps tooling and infrastructure-as-code (Terraform, CI/CD, Docker, Kubernetes).
Proven ability to bridge technical and financial domains, collaborating effectively with investment and research professionals.
Familiarity with financial data structures (e.g. fundamentals, portfolio metrics, ESG data, market data) and reporting standards.
(Preferred) Practical exposure to AI/ML applications in finance - e.g., LLM integration, data enrichment, or predictive modeling.

Why Join?

This role offers the opportunity to lead data engineering within a firm where technology and investment strategy are deeply intertwined. You’ll work with exceptional technologists and investors, shaping the data platform that fuels next-generation asset management.

If you are a seasoned data engineer with a passion for AI-driven finance, we’d welcome a confidential discussion to explore this opportunity further.