Python Developer
Tribus is hiring a Python/Quant Infrastructure Engineer for a leading global hedge fund's Hong Kong office. Day to day: building Python services and data pipelines (migrating Airflow to Kubernetes), CI/CD and testing, plus trading-facing tools like backtesting platforms, dashboards, options analytics and AI-powered trading apps.
- Compensation
- Not disclosed
- Location
- Hong Kong, Hong Kong
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Full time
- Experience
- 3+ years
- Category
- Software engineering
- Posted
Skills
Must have
- 3+ years of software engineering experience, ideally in financial services, quantitative trading or another data-intensive environment
- Hands-on experience with Kubernetes, Docker, Airflow and CI/CD
- Experience developing scalable services, data pipelines and production applications
- Exposure to front-end development, GUIs or internal tooling using React, Angular or similar frameworks
- Strong problem-solving skills and ability to take ownership of technical projects
Nice to have
- Familiarity with Java or C#
- Experience within hedge funds, proprietary trading, investment banking or quantitative finance
- Understanding of financial markets, particularly options, derivatives or systematic trading
- Experience building backtesting systems, trading applications or quantitative research tools
- Exposure to AI/ML frameworks and data-driven applications
Full description
Location: Hong Kong
Industry: Quantitative Trading / Hedge Funds
Employment: Permanent
Relocation: International relocation supported
The Opportunity
Tribus is partnering with a leading global hedge fund to hire a Python / Quant Infrastructure Engineer for its Hong Kong office.
This is an opportunity to join a highly technical quantitative trading team responsible for developing the infrastructure, data platforms and applications supporting global trading strategies.
The role combines Python software engineering, infrastructure development and trading-facing applications, working closely with quantitative researchers and portfolio managers.
Unlike a traditional infrastructure or DevOps position, this is a hands-on software engineering role with significant ownership across platform architecture, data systems and internal trading tools.
Key Responsibilities
- Design and develop scalable services, including migrating existing Airflow workflows to Kubernetes-based infrastructure.
- Build and maintain Python applications, CI/CD pipelines and automated testing frameworks.
- Develop and optimise large-scale data pipelines, including data lifecycle management, monitoring and quality controls.
- Build backtesting platforms, dashboards and visualisation tools used by quantitative researchers and portfolio managers.
- Develop trading-facing applications supporting options analytics, strategy analysis and live trading workflows.
- Contribute to the development of AI-powered trading applications.
- Manage compute resources, production monitoring and infrastructure performance.
Technical Requirements
- 3+ years of software engineering experience, ideally within financial services, quantitative trading or another data-intensive environment.
- Hands-on experience with Kubernetes, Docker, Airflow and CI/CD.
- Experience developing scalable services, data pipelines and production applications.
- Exposure to front-end development, GUIs or internal tooling using React, Angular or similar frameworks.
- Familiarity with Java or C# would be advantageous.
- Strong problem-solving skills and the ability to take ownership of technical projects.
Highly Desirable
- Experience within hedge funds, proprietary trading, investment banking or quantitative finance.
- Understanding of financial markets, particularly options, derivatives or systematic trading.