Global Equity Data Engineer – Quantitative Long/Short Strategy

Location: Singapore / Shanghai / Hong Kong (TBD)

We are a leading technology-driven investment firm specializing in systematic long/short equity strategies across global markets. Leveraging advanced research, machine learning, and real-time market data, we generate alpha at scale and are expanding our global equities infrastructure.

We are seeking a Global Equity Data Engineer to build and maintain robust data pipelines that support our portfolio managers and quantitative researchers. This is an exceptional opportunity to join a fast-growing, international team and work across multiple markets and strategies.

Key Responsibilities:

1. Ingest, standardize, and maintain global equity datasets from multiple vendors (e.g., Bloomberg, Refinitiv, FactSet, S&P Global, Exegy)
2. Align and structure data to support quantitative research, factor modeling, and portfolio construction
3. Track and handle complex corporate actions including mergers, spin-offs, ticker changes, delistings, and dual listings
4. Collaborate with PMs, quantitative researchers, and trading infrastructure engineers to define data requirements
5. Develop and maintain robust mappings across exchanges, prime brokers, and OMS/EMS systems
6. Ensure data quality through validation, monitoring, and anomaly detection

Required Qualifications:

1. 3+ years of experience in data engineering or quantitative data operations at a hedge fund, proprietary trading firm, or asset manager
2. Deep understanding of global equity markets (North America, Europe, Asia-Pacific)
3. Strong programming skills in Python (Pandas, NumPy) and SQL
4. Experience with corporate action handling and security identifier mapping (ISIN, CUSIP, SEDOL, RIC, Bloomberg Ticker)
5. Familiarity with data pipeline orchestration tools (e.g., Airflow, Luigi) and financial reference/pricing data
6. Ability to navigate prime brokerage data and internal ticker mapping for execution and post-trade reconciliation

Preferred Qualifications:

1. Experience with tick- or bar-level intraday equity data
2. Knowledge of distributed data frameworks (Snowflake, Spark)
3. Exposure to quantitative alpha research, portfolio risk modeling, or buy-side OMS/EMS systems

Why Join Us:

1. Fast-growing quantitative investment team.
2. Work in a highly international, tech-focused environment
3. Gain exposure to multiple markets, strategies, and asset classes
4. Opportunity to grow with the business and contribute to global expansion
5. Work alongside experienced PMs and researchers using cutting-edge technology
6. Sponsorship for work passes available for eligible candidates