- Location
- Hong Kong; Singapore · Hong Kong · Singapore
- Department
- Data Platform
- Seniority
- Senior
- Experience
- 5+ years
- Source
- Greenhouse
Description
Role Responsibilities
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End-to-End Data Lifecycle Management: Independently spearhead the full-lifecycle pipeline development for high-frequency historical MBO (Market-By-Order) data across one or more core markets. Responsibilities span vendor sample evaluation, high-performance PCAP parser development, full-scale historical backfilling, high-standard data quality verification (Sanity Checks), and production-ready delivery.
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Data Sourcing & Proactive Quality Control: Leverage deep data engineering expertise to lead or deeply participate in the evaluation and technical onboarding of high-frequency market data vendors. Proactively identify and assess data quality risks (e.g., known gaps, packet loss, bandwidth/frequency coverage) prior to procurement, minimizing the cost of redundant purchasing and rework from the source.
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Exchange Architecture & Pitfall Mitigation: Utilize a profound understanding of market microstructure and raw exchange feeds to precisely identify and resolve structural pitfalls during the design and acceptance phases (e.g., CME Implied Orders, symbol mapping, sequence number discontinuity, and timestamp precision), ensuring early convergence of data defects.
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New Market Onboarding & Protocol Adaptation: Lead the market data onboarding, micro-protocol parsing, and standardized normalization at the MBO level for new global exchanges and trading systems.
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Multi-Source Cross-Validation Framework: Build a multi-dimensional, multi-granular data cross-validation framework (including but not limited to MBO vs. TAQ, Bloomberg historical data, and Raw PCAP vs. Normalized Data) to guarantee absolute data accuracy, consistency, and robustness.
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Team Empowerment & Standardization: Responsible for mentoring junior engineers and talent pipeline development. Cultivate and institutionalize team-level sanity check protocols, high-frequency data engineering best practices, and standardized delivery whitepapers.
Requirements
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Experience & Background: 5+ years of experience in global exchange market data/tick data engineering, with a proven track record of successfully implementing full-lifecycle, large-scale historical MBO data projects across multiple markets.
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Core Technical Stack: Highly proficient in C++ with exceptional capabilities in native PCAP processing and low-level raw data parsing. Deep understanding of high-frequency market microstructure, with hands-on mastery of Order Book Reconstruction, Snapshot Recovery, and latency-sensitive data alignment techniques (e.g., A/B arbitrage alignment).
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Vendor Evaluation Expertise: Extensive practical experience in direct exchange feeds and major international third-party market data vendors (e.g., MayStreet, Pico, Databento, Refinitiv, QuantHouse). Proven ability to conduct vendor selection, sample evaluation, and quality differentiation, with a clear understanding of the underlying pain points and technical nuances of various data sources.
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Domain Knowledge: Profound understanding of the underlying market data architectures of major global exchanges. Familiar with the characteristics of market data across various asset classes (with an emphasis on global derivatives/futures). Possess hands-on, practical experience in resolving critical pitfalls such as implied order processing, contract symbol mapping mechanisms, sequence number continuity validation, and multi-precision price alignment.
Skills
Data EngineeringProcurement
