Job Description

Systematic Hedge Fund. 6 months, strong likelihood of extension.

A systematic hedge fund is seeking a Quant Data Engineer to own the onboarding, normalisation and integration of alternative data sources — satellite imagery, NLP/news feeds, web-scraped data, and ESG signals — into their quantitative research environment. You will work directly with quant researchers to ensure alternative data is clean, correctly licensed, and accessible in the research platform in a form researchers can actually use.

This role requires data engineering experience gained within a systematic hedge fund, quant asset manager, or financial services firm where alternative data is used in a live investment research context. General data engineering from tech, e-commerce, or enterprise environments is not sufficient. If you have not previously worked on data pipelines that feed directly into quantitative investment research or systematic trading strategies, this role is unlikely to be the right fit.

What they need:

→ 4+ years data engineering within a systematic hedge fund, quant asset manager, or financial services firm -building pipelines that feed into live quantitative research or investment processes

→ Direct experience onboarding and normalising alternative data sets NLP/news, satellite, web, ESG, or transaction data, for use in systematic research

→ Strong Python — data pipeline tooling, data quality frameworks, Pandas/Polars for financial time-series

→ Cloud data infrastructure: S3, Athena, Snowflake, or Databricks in a research context

→ Understanding of data licensing, vendor entitlements, and data governance requirements in a regulated investment context

→ Experience working directly with quant researchers — translating raw data into research-ready formats

→ KDB+/q familiarity beneficial

Duration: 6 months.