Data Platform Engineer (Python / Rust) | Top Buy-Side Firm | HKD 60-100K
Build and maintain an enterprise-grade data platform for a global quantitative investment firm in Hong Kong: monitoring dataset quality, alerting on production issues, integrating with trading pipelines, and supporting cross-functional teams. Core stack is Python or Rust with Kubernetes, Docker, and cloud orchestration.
- Compensation
- HK$60K–HK$100K / mo
- Location
- Hong Kong, Hong Kong
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- Not specified
- Category
- Data engineering
- Posted
Skills
Must have
- Bachelor's or Master's degree in Computer Science, Software Engineering, or a related quantitative field
- Strong Computer Science fundamentals with hands-on proficiency in Python or Rust
- Hands-on experience with Kubernetes, containerization (Docker), and cloud orchestration
- Self-starter mindset with ability to work autonomously in a distributed global team
- Strong verbal and written communication skills
Nice to have
- Experience working with financial data or within quantitative finance / high-frequency trading environments
- Exposure to modern data quality frameworks (e.g., Great Expectations, Soda)
- Experience developing custom front-end monitoring dashboards or data visualization tools
Full description
We are partnering with a premier global quantitative and systematic investment manager to recruit a Python / Rust Systems Engineer – Data. Operating across all major liquid asset classes globally, our client relies on a cutting-edge, data-driven, and scientific approach to trading.
Responsibilities:
Platform Development & Observability: Design, build, and maintain an enterprise-grade data platform that monitors dataset quality, validates correctness, and alerts stakeholders to critical production issues in real time.
Core Libraries & Onboarding: Develop and optimize shared engineering libraries used across data functions to streamline and accelerate the onboarding of new datasets.
Cross-System Integrations: Architect, build, and document integrations with downstream engineering tools and trading workflows for seamless alerting and pipeline management.
Developer Advocacy & Support: Guide cross-functional teams on platform best practices, assist with code migrations, and lead deep-dive debugging and troubleshooting for platform issues.
Cross-Functional Collaboration: Partner closely with quantitative researchers, traders, and platform engineers globally to deliver scalable, high-throughput solutions.
Requirements:
Education: Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related quantitative field.
Core Tech Stack: Strong Computer Science fundamentals with hands‑on proficiency in Python or Rust.
Infrastructure & Cloud: Hands‑on experience with Kubernetes, containerization (Docker), and cloud orchestration.
Problem‑Solving & Communication: Self-starter mindset with the ability to work autonomously in a distributed global team, alongside strong verbal/written communication skills.
Nice-to-Haves / Bonus Points:
Experience working with financial data or within quantitative finance / high‑frequency trading environments.
Exposure to modern data quality frameworks (e.g., Great Expectations, Soda).
Experience developing custom front‑end monitoring dashboards or data visualization tools.
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