About the Opportunity

Our client is a fast-growing, data-driven quantitative investment firm based in Hong Kong that leverages modern technology and high-performance engineering to power its trading strategies and quantitative research.

To support the continued expansion of their platform, the firm is seeking a hands-on Data Engineer / Data Specialist to join their technical team. This role is ideal for a technologist with strong core software engineering fundamentals who wants to take end-to-end ownership of data infrastructure, financial datasets, and data storage systems.

Whether a your strength lies in database query optimization, automated data ingestion pipelines, or financial dataset analysis, the firm values strong technical problem-solvers who enjoy building practical solutions from the ground up.

Key Responsibilities

(The candidate will take ownership of 1–2 primary areas initially, with room to expand scope over time)

• Financial Domain Analysis & Feature Creation: Develop a deep understanding of unique financial data feeds (market data, vendor feeds, alternative datasets) to structure fields, enforce domain conventions, and construct derived research datasets.
• Database Management & Performance Optimization: Architect, manage, and optimize data storage layers, ensuring high query speeds while keeping infrastructure costs controlled.
• Production Operations & Data Quality: Oversee data hygiene, automated monitoring, alerting, and pipeline maintenance to guarantee high reliability for research models.
• Dataset Documentation & Knowledge Sharing: Standardize documentation and toolkits for all ingested datasets, enabling quantitative researchers to seamlessly explore and query data independently.
• Data Ingestion & Feed Onboarding: Build, maintain, and scale robust data pipelines that ingest and transform raw vendor and exchange feeds into clean, production-ready research assets.

Candidate Qualifications

• Engineering & Coding Core: Strong programming proficiency in Python (or another core language) with an emphasis on writing clean, scalable, and maintainable code.
• Practical & Agile Mindset: A builder who prefers simple, pragmatically scalable solutions over overly complex abstractions, with high learning agility to adopt new tools quickly.
• Production Pipeline Experience: 3+ years of experience building or managing production data pipelines, ideally dealing with financial/market data, crypto live feeds, or high-throughput datasets.
• Communication & Growth: Excellent spoken and written English, with the enthusiasm to learn and pick up new technical and domain responsibilities in a fast-paced trading environment.
• Educational Background: Bachelor's degree in Computer Science, Software Engineering, Quantitative Finance, or equivalent practical experience.

Why Consider This Role?

• No Rigid Tool Requirements: While experience with tools like Snowflake, ClickHouse, or PySpark is a plus, the firm prioritizes strong technical fundamentals and learning agility over specific tool familiarity.
• Direct Business Impact: Engineers work directly alongside quantitative researchers and system architects, seeing the immediate impact of their infrastructure on live trading.