Data Engineer (Financial Data / West)
Summary
Builds and maintains global equity datasets for quant research and portfolio construction, using Python, SQL, and data pipeline tools.
Responsibilities
- Ingest, standardize, and maintain global equity datasets from multiple third-party data vendors.
- Structure and align datasets to support quantitative research, factor modeling, and portfolio construction.
- Develop and maintain systems to manage corporate actions such as ticker changes, mergers, spin-offs, and listings.
- Collaborate with portfolio managers, quantitative researchers, and engineers to define and deliver data requirements.
- Manage ticker mapping across prime brokers, trading venues, custodians, and OMS/EMS platforms.
- Ensure data integrity through validation processes, monitoring pipelines, and anomaly detection.
- Maintain and enhance symbol mapping libraries across exchanges, asset classes, and time zones.
Requirements
- Bachelor’s degree or above in Computer Science, Engineering, or a related field.
- Proficiency in Python (e.g., Pandas, NumPy) and SQL.
- Experience with data pipeline orchestration tools such as Airflow or Luigi.
- Familiarity with financial data vendors and handling reference and pricing datasets.
- Strong knowledge of global equity markets across North America, Europe, and Asia-Pacific.
- Solid understanding of market microstructure and security identifiers (e.g., ISIN, CUSIP, SEDOL, RIC, Bloomberg Ticker).
- Background in data engineering or quantitative data operations within financial institutions is advantageous.