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.
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or continue with email
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.
#J-18808-Ljbffr
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