Quantitative Developer (Data)

Responsibilities: Data Engineering & Pipelines: Design and implement robust ETL (Extract, Transform, Load) pipelines to process and deliver large-scale datasets efficiently. Data Quality & Monitoring: Develop and maintain data Quality Control (QC) systems and monitoring tools, ensuring the integrity and reliability of data across production and research environments. Collaboration & Integration: Partner with internal research and technology teams to seamlessly integrate new and diverse datasets

Gravitas Recruitment Group - Hong Kong - Full time

Salary: HKD50000 - HKD90000 per month

Responsibilities:

  • Data Engineering & Pipelines: Design and implement robust ETL (Extract, Transform, Load) pipelines to process and deliver large-scale datasets efficiently.
  • Data Quality & Monitoring: Develop and maintain data Quality Control (QC) systems and monitoring tools, ensuring the integrity and reliability of data across production and research environments.
  • Collaboration & Integration: Partner with internal research and technology teams to seamlessly integrate new and diverse datasets into existing systems.
  • Quantitative Analytics Tools: Develop frameworks for the systematic back-testing and signal analysis of quantitative trading strategies.
  • Portfolio Analysis: Create sophisticated analytics tools and interactive dashboards for comprehensive portfolio risk assessment and performance attribution.
  • Infrastructure Management: Oversee the configuration and ongoing maintenance of container orchestration environments.
Required Technical Qualifications, Skills, and Experience:
  • Education: Bachelor's degree in Computer Science, Engineering, or a related technical discipline.
  • Programming Languages & Libraries: High proficiency in C/C++ and Python, along with essential data processing libraries (e.g., Pandas, Polars, NumPy).
  • Database Technologies: Expertise in various database products, including MySQL, MongoDB, and ClickHouse.
  • Backend & Concurrency: Strong knowledge of backend data storage technologies, multi-processing, and multi-threading programming techniques.
  • Distributed Systems: Practical experience with parallel computing, distributed systems, and cloud service providers such as AWS.
  • Financial Product Knowledge: Familiarity with asset classes including equities, derivatives, and fixed income.
  • Soft Skills: Strong organizational skills, keen attention to detail, excellent communication (written and verbal), self-motivation, and the ability to work both independently and collaboratively within a team.










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