An exceptional opportunity to join a successful hedge fund as a Data Engineer where you'll build the data backbone powering advanced investment strategies. This is not a vanilla data role. The team need someone who genuinely understands either equities or commodities (preferably both) products – how each is priced and valued, the market events and behaviours that affect them, and the full operational trade lifecycle. You'll act as the data lead for the asset class build-out, helping to upskill the wider team (from a data perspective rather than analytics) and setting the standard for how this data is sourced, modelled, governed, and consumed.
You'll be exposed to the full data flow – ingestion, cleaning, quality assurance, and the build-out of robust data platforms – managing diverse financial datasets spanning market, fundamental, and alternative sources from acquisition through to delivery. Working closely with quant researchers, traders, and engineers, you'll solve complex data challenges and deliver high-quality data to fuel sophisticated trading models in a fast-paced, innovative environment.
Responsibilities
* Develop a deep working understanding of equities and commodities products – pricing, valuation, market behaviour, key events, and the full operational trade lifecycle – and apply that knowledge to data design, modelling, and governance.
* Act as the data lead for the asset class build-out, partnering closely with the newly hired Equities Trader and the incoming Commodities Trader, and helping to upskill the wider team on best practice for handling this data.
* Collaborate with vendors to source and integrate complex datasets, ensuring they meet the firm's exacting standards for trading and research.
* Design and maintain scalable data pipelines that transform raw data into analysis-ready formats, applying top-tier engineering practices for seamless integration with trading systems.
* Build robust validation tooling to ensure data accuracy, timeliness, and integrity in support of quantitative strategies.
* Provide hands-on support for data pipelines, swiftly resolving issues to maintain uninterrupted data flow for trading operations.
Requirements
* 5+ years of experience building ETL/ELT pipelines with Python and pandas in a financial markets trading environment.
* Genuine product knowledge of equities and/or commodities – including how each is priced and valued, the events and market behaviours that drive them, and the operational trade lifecycle.
* Strong expertise in relational databases and SQL.
* Proficiency with technologies such as S3, Kafka, Airflow, or Iceberg.
* Demonstrated experience managing large, complex financial datasets sourced from multiple vendors.
* Confidence working with a team that is newer to these asset classes, bringing the data perspective and lifting the standard around them.
* A passion for engineering excellence and delivering impactful, practical solutions.
* Excellent collaboration and communication skills to thrive in a team environment.