Data Engineer

MS Capital is a private fund management company with a strong founding team with long-accumulated experience in strategy modelling, trading system and platform development. Using advanced artificial intelligence technology as the cornerstone, and enforcing strict investment management, the company's investment fund has gained sustained and stable returns.

You will be joining MS Capital's technology arm, with AL/ML as its cornerstone, and is committed to providing users with high-quality and stable trading services. The company now has a number of experienced quantitative researchers, world-class deep learning scientists and engineers from leading internet companies and top universities. The company has also provided various kinds of trading solutions for a number of leading brokerage firms and organizations. The company's vision is to integrate artificial intelligence technology with quantitative investment scenarios, relying on strong artificial intelligence R&D capabilities and advanced trading strategy models, to provide users with comprehensive and stable investment service.

As a Data Engineer on the Long/Short Equities team, you will be responsible for ingesting, cleaning, and aligning data from various global vendors and prime brokers. Your role will be central to ensuring our signals, backtests, and live trading systems operate on high-quality and accurate data across the full lifecycle of a security.

Roles & Responsibilities:

• Ingest, standardize, and maintain global equity datasets from multiple third-party vendors (e.g., Bloomberg, Refinitiv, FactSet, S&P Global, Exegy, etc.).
• Structure and align data to support quantitative research, factor modeling, and portfolio construction.
• Develop systems to track and handle complex corporate actions including ticker changes, delistings, mergers, spin-offs, dual listings, ADR/local shares.
• Collaborate closely with PMs, quantitative researchers, and trading infrastructure engineers to define and fulfill data requirements.
• Understand prime brokers’ internal ticker conventions and develop robust mappings across trading venues, custodians, and OMS/EMS systems.
• Ensure data quality through rigorous validation, monitoring pipelines, and anomaly detection.
• Help maintain symbol mapping libraries across time zones, exchanges, and asset classes.

Qualifications:

• Bachelor's degree or above in Computer Science, Engineering or related field.
• Deep familiarity with global equity markets, including North America, Europe, and Asia-Pacific exchanges.
• Proficient in Python (Pandas, NumPy), SQL, and data pipeline orchestration tools (e.g., Airflow, Luigi).
• Knowledge of major data vendors and experience working with financial reference and pricing data.
• Strong understanding of market microstructure and security identifiers (e.g., ISIN, CUSIP, SEDOL, RIC, Bloomberg Ticker).
• Ability to navigate prime brokerage data and internal ticker mapping for order execution and post-trade reconciliation.
• Experience in a data engineering or quantitative data operations role at a hedge fund, proprietary trading firm, or asset manager.
• Prior experience working with tick- or bar-level data, especially for intraday equity strategies.
• Familiarity with buy-side OMS/EMS systems and order flow handling.