Data Engineer
Core
Ingesting, cleaning, and aligning global equity data to support quantitative research, factor modeling, and live trading systems.
Role type
Data Engineer (Quantitative Finance)
Builds
Data pipelines for signals, backtests, and trading infrastructure
Domain
Quantitative investment / Financial data infrastructure
Deliverable
production ML models | infrastructure
Required skills
Python (Pandas, NumPy), SQL, data pipeline orchestration (Airflow, Luigi), global equity market knowledge, financial reference data handling, market microstructure understanding, security identifier mapping (ISIN, CUSIP, SEDOL, RIC)
Preferred skills
Experience with prime brokerage data, knowledge of corporate actions handling
Technologies
Bloomberg, Refinitiv, FactSet, S&P Global, Exegy, Airflow, Luigi
Responsibilities
Ingest and standardize global equity datasets from third-party vendors; Structure and align data for quantitative research and portfolio construction; Develop systems to track complex corporate actions; Collaborate with PMs and researchers to define data requirements; Map internal ticker conventions across trading venues and OMS/EMS systems; Ensure data quality through validation and anomaly detection; Maintain symbol mapping libraries across time zones and exchanges.