Market Data Engineer
Summary
Data Engineer at a multi-strategy hedge fund in London, building and improving the data platform behind investment strategies. Day to day: sourcing, validating and integrating vendor financial datasets, and building data products for PMs, quants and risk teams using Python, SQL and cloud warehouses like Snowflake, Redshift or BigQuery.
Data Engineer | Multi-Strategy Hedge Fund
London | Global Investment Platform
Data sits at the heart of how this hedge fund invests, and they're looking for a Data Engineer to help strengthen the infrastructure behind its investment strategies.
You’ll work closely with Portfolio Managers, Quants and Risk teams, building data products that help them research opportunities, test strategies and make informed investment decisions.
The focus is on getting complex financial data right — from vendor feeds and data quality through to integration, scalability and performance. Your work will directly influence how investment teams access and use data across the business.
The opportunity:
- Work close to the investment process, supporting PMs, quants and risk teams.
- Own the sourcing, validation and integration of financial datasets from external vendors.
- Build robust data products that improve the quality and usability of data across investment strategies.
- Improve the reliability and performance of the firm's core data platform.
- Help shape how the platform evolves as the business and its investment needs grow.
What they're looking for:
- 4+ years' experience in financial services, ideally within a hedge fund or a Front Office / Quant environment.
- Strong Python and SQL, with C++ experience beneficial.
- Experience with Snowflake, Redshift or BigQuery, alongside cloud-based data infrastructure.
- Hands-on experience with data pipelines, orchestration, production monitoring and automated data quality.
- An understanding of market data, reference data and how financial datasets are used within investment workflows.
Why this role?
This is a chance to move beyond building pipelines in isolation and work on the data infrastructure that underpins investment research and portfolio management.