Senior Market Data Engineer
Summary
Builds and maintains high-frequency market data pipelines for global exchanges, reconstructing order books and ensuring low-latency, high-quality data for trading and research.
Job Requirements 5+ years of engineering experience in global exchange market/tick data. We are looking for an expert in exchange market data who possesses deep practical experience in either of the following tracks: (a) Real-Time Connectivity Track: Proficient in multi-exchange real-time feed handler connectivity; deeply familiar with multicast, snapshot recovery, and A-B arbitrage data alignment/low-latency processing techniques. (b) Historical Data Track: Proficient in the full historical MBO data lifecycle; hands-on experience in high-performance Pcap parser development, underlying order book reconstruction, full historical data backfilling, and high-standard data cleaning/validation. Core Tech Stack: Expert-level C++ with exceptional capabilities in native Pcap and raw data processing; highly proficient in order book reconstruction mechanisms. Domain Knowledge: Deeply understand the underlying market data architectures of major global exchanges; familiar with market data characteristics across different asset classes (especially global derivatives/futures); hands-on experience solving critical traps like implied order matching, contract symbol mapping, and sequence number continuity.
Preferred Qualifications Complementary Market Experience: Deep experience in global derivatives/futures MBO data, or hands-on experience in market data processing and protocol connectivity for core APAC markets such as HKEX and JPX/TSE. Collaborative Vendor Evaluation: Experience in evaluating data samples from international market data vendors (e.g., Pico, Databento, Maystreet, Refinitiv, Quanthouse, etc.) to assist the team with technical admission and identifying underlying data gaps/pain points. Engineering Toolchain: Experience in building in-house high-standard sanity check or data quality monitoring frameworks; proficient in using Python for efficient data analysis and auxiliary processing.