Data Engineer

Data Engineer – Quantitative Data PlatformLocation: LondonCompensation: Up to £200,000 base + performance bonusI’m working with a leading investment firm in London that is looking to hire an experienced Data Engineer to help build and scale a high-performance data platform supporting quantitative investment teams.This is a highly technical engineering role focused on large-scale data infrastructure, backtesting and research workloads. You’ll be working with petabyte-scale datasets and partnering closely with quantitative engineers and researchers.What you’ll be working on:Building and scaling data infrastructure for backtesting and other data-intensive applicationsDeveloping ingestion and ETL pipelines operating across petabyte-scale datasetsSolving challenges around data quality, storage, backfills and high-performance data consumptionDesigning batch and streaming data architecturesWorking closely with quantitative researchers and engineering teamsImproving the scalability, reliability and performance of distributed data systemsWhat we’re looking for:5+ years of experience in data-intensive engineeringStrong SQL and database expertise, particularly with large-scale or time-series datasetsStrong programming skills in Python, Rust and/or C++Experience with tools such as Pandas, Polars, Dask or PySparkExperience building data platforms, ETL systems, data lakes, warehouses or lakehouse architecturesKnowledge of Parquet, Arrow or similar columnar formatsExperience with distributed systems technologies such as Kafka and RedisStrong understanding of performance optimisation and debuggingNice to have:ClickHouse, Snowflake or similar technologiesFinancial markets / quantitative investment experienceREST API developmentPrometheus, Grafana or SentryWhy join?You’ll have the opportunity to work on genuinely large-scale data engineering problems where performance and reliability matter, while building infrastructure used directly by quantitative investment teams.Compensation: £140,000 to £200,000 base + bonusLocation: London