We are seeking a highly motivated Python Data Developer (Quantitative Operations) to join the firm's Hong Kong-based team. This is a unique opportunity for a junior data professional to step into a high-ownership role, acting as a primary technical partner for the Global Operations and Business Management teams.
You will be designing and building the critical data pipelines and automation frameworks that ensure the firm’s operational accuracy. Please note: This is an operations technology and data automation role, not an AI, Machine Learning, or low-latency C++ infrastructure position.
Key Responsibilities
• Strategic Partnership: Act as the trusted technical partner for the Business Operations teams, translating daily operational bottlenecks into robust Python solutions.
• Data Pipelines & ETL: Build, maintain, and scale data extraction and transformation pipelines connecting to various financial APIs and internal databases.
• Reconciliation Automation: Design Python/Pandas scripts to replace manual Excel-based workflows, ensuring 100% data accuracy between internal systems and external prime brokers.
• Platform Evolution: Contribute new features to the firm’s internal web application suite, creating high-impact reports and automated monitoring dashboards.
Your Profile
• Experience: 1–3 years of professional experience, ideally within Trade Support, Middle Office Technology, or Operations Data Engineering at a financial institution.
• Tech Stack: Expert proficiency in Python is a must, specifically for heavy data manipulation using Pandas and Numpy.
• Data Skills: Strong understanding of SQL, database management, and building ETL pipelines.
• Problem Solver: A highly pragmatic individual who enjoys troubleshooting complex data breaks and delivering immediate business value.
• Education: Degree in Computer Science, Data Science, Finance, or a related quantitative field.
