Public summary
Seeking a Data & Platforms Engineer to design, build, and maintain internal data products that support investment and research teams in a leading European asset management firm. Responsibilities include developing data pipelines, APIs, and tools using Python, SQL, and AWS technologies. The role involves close collaboration with investment and AI teams and emphasizes the use of AI-assisted engineering practices. The position offers a highly international team environment in Berlin with visa sponsorship and relocation support.
Location and work setup
- Location
- Berlin
- Remote status
- On-site
- German requirement signal
- No German Required Detected
- Detected job language
- English
Responsibilities
Design, develop, and operate internal data products including data pipelines, datasets, APIs, and tooling to support investment and research teams. Work closely with stakeholders to gather requirements, prioritize tasks, and communicate technical trade-offs clearly. Implement reliable, secure, and maintainable data pipelines and integrations handling complex financial data. Promote engineering best practices such as automated testing, CI/CD, code reviews, and documentation. Enhance operational excellence with observability, monitoring, and data quality management. Utilize agentic AI tools throughout engineering processes to improve productivity and code quality.
Qualifications
3-5 years of professional software or data engineering experience, with strong skills in Python and SQL. Proven experience in building production-grade systems with good software engineering discipline including testing and CI/CD. Ability to communicate complex technical concepts clearly to non-engineers. Experience using AI tools in software development is highly desirable. Knowledge or interest in investment, financial markets, and data. Familiarity with technologies like Databricks, PySpark, orchestration tools (Airflow, Dagster), lakehouse formats (Parquet, Delta, Iceberg), and AWS is a plus.