About this role
Senior / Mid-Level Data Engineer (Financial Data & Pipelines)
Job Description:
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
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The candidate will take ownership of 1–2 primary areas initially, with room to expand scope over time
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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.
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Database Management & Performance Optimization: Architect, manage, and optimize data storage layers, ensuring high query speeds while keeping infrastructure costs controlled.
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Production Operations & Data Quality: Oversee data hygiene, automated monitoring, alerting, and pipeline maintenance to guarantee high reliability for research models.
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Dataset Documentation & Knowledge Sharing: Standardize documentation and toolkits for all ingested datasets, enabling quantitative researchers to seamlessly explore and query data independently.
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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.
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Candidate Qualifications
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Engineering & Coding Core: Strong programming proficiency in Python (or another core language) with an emphasis on writing clean, scalable, and maintainable code.
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Practical & Agile Mindset: A builder who prefers simple, pragmatically scalable solutions over overly complex abstractions, with high learning agility to adopt new tools quickly.
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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.
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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.
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Educational Background: Bachelor's degree in Computer Science, Software Engineering, Quantitative Finance, or equivalent practical experience.
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Why Consider This Role?
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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.
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Direct Business Impact: Engineers work directly alongside quantitative researchers and system architects, seeing the immediate impact of their infrastructure on live trading.
Required Skills
- Performance
- Data
- Support
- Database
- Database Management
- Financial Data
- Data Quality
- Architects
- Pipelines
- Trading
- Operations
- Ownership
- Analysis
- Snowflake
- Onboarding
- Storage
- Reliability
- Optimization
- Agile
- Infrastructure
- Writing
- Programming
- Computer Science
- Software
- Research
- Finance
- Documentation
- Maintenance
- Engineering
- Business
- English
- Science
- Python
- Communication
- Management