Quantitative Developer (Data Engineering)

Based in Central, Hong Kong, our client is a premier, tech-forward quantitative fund managing global cross-asset portfolios within a merit-driven culture that balances elite performance with continuous learning, mutual respect, and work-life balance.

ROLE: Quantitative Developer (Data Engineering)

Key Responsibilities

• Pipeline Engineering: Architect and manage high-throughput Python/cloud ETL systems for massive financial data streams.
• Performance Tuning: Detect infrastructure bottlenecks to accelerate data ingestion and distribution speeds.
• Data Integrity: Build automated quality-assurance monitors and outlier-detection tools for research and live trading.
• Research Support: Partner with quants to clean, structure, and onboard novel alternative data sources.
• Risk Analytics: Construct interactive visualization dashboards for portfolio attribution and risk modeling.
• System Monitoring: Oversee daily pipeline health to guarantee punctual data delivery.

Technical Profile

• Education: University degree in a highly technical STEM discipline.
• Python Mastery: Expert coder focused on optimization, using Polars, Pandas, and NumPy for heavy data manipulation.
• Database Stack: Strong command of relational and columnar engines, including ClickHouse, MySQL, and Elasticsearch.
• Cloud Infrastructure: Hands-on experience deploying data pipelines via AWS ecosystems (S3, Athena).
• Market Knowledge: Basic comprehension of core instruments like equities, FX, fixed income, and derivatives.
• Soft Skills: Autonomously driven professional with sharp organizational and cross-team communication abilities.