Quant Developer

We are working with a fast-growing quantitative investment fund at an early but well-capitalised stage, looking to hire a Quant Developer / Data Engineer to help build and scale their data platform supporting systematic equity and futures strategies. This is a highly technical role sitting close to the investment process, offering real ownership over market data infrastructure used in both research and live trading.As a Quant Developer / Data Engineer, you will play a key role in the acquisition, ingestion, and processing of large-scale financial datasets. You’ll work closely with quantitative researchers to ensure data is robust, clean, and production-ready.Key responsibilities include: Designing and maintaining data pipelines for market and alternative data Supporting historical backtesting and production deployment across equities and futures Managing data quality, validation, and versioning Optimising storage and retrieval for research and live systems Contributing to scalable, low-latency infrastructure in a startup environmentWe’re looking for candidates with a strong background in financial data engineering, ideally within systematic trading or quant research environments. You should have experience with: Equity statistical arbitrage datasets, including core market data (Bloomberg, Refinitv, FactSet) Working with alternative datasets (e.g. fundamentals, events, sentiment, signals) Large-scale time series data and cross-sectional datasets Building data systems that support both research and production workflowsTechnical Skills Strong programming skills (Python essential; C++/Java a plus) Experience with databases, data lakes, or columnar storage Familiarity with cloud-based or distributed systems Solid understanding of market data structures for equities and futuresWhy Join? Start-up culture with genuine roadmap to $1billion AUM Equity on offer alongside excellent base plus bonus Machine learning is core to the investment process, not an overlay Exposure to multiple asset classes within a unified research framework Opportunity to influence model design, data architecture and research standards