Data Engineer – Research Platform
Summary
Designs and scales ETL pipelines to clean and structure APAC equity market data for fundamental research and AI-driven investment models.
My client is a leading Macro-driven investment platform, they are seeking a high-caliber Data Engineer to architect and scale the next-generation data foundation for their fundamental equity research.
In this role, you will transform complex, high-volume financial feeds—with a strong emphasis on APAC equity markets—into clean, structured datasets that directly power portfolio managers, research analysts and downstream AI applications.
Key Responsibilities
- Pipeline Architecture & Ingestion: Design, deploy, and optimize scalable ETL/ELT pipelines to ingest, clean, and standardize diverse financial and market datasets.
- APAC Market Specialization: Manage, structure, and model APAC equity market data, leveraging extensive hands-on expertise with feeds, APIs, and data structures.
- Data Normalization & Entity Resolution: Solve complex, real-world market data challenges—including mapping company entities, ticker transitions, corporate actions, and time-series alignment.
- Data Governance & Quality Control: Implement robust monitoring, schema designs, lineage tracking, and automated testing to guarantee high data reliability and uptime.
Core Qualifications
- 3+ years of experience in data engineering, data platform architecture, or financial data management.
- Advanced proficiency in Python and SQL.
- Experience working with market data, company data, fundamentals, estimates, or related financial datasets.
- Experience integrating major market data providers (e.g., Bloomberg, FactSet, LSEG/Refinitiv).
- Background in supporting hedge funds, prop trading desks, or buy-side equity research teams would be a bonus.