Senior Market Data Engineer (Hong Kong/Singapore)
Summary
Build and maintain high-frequency market data pipelines for derivatives exchanges, parsing raw PCAP feeds and reconstructing order books in C++ to ensure ultra-low-latency, high-accuracy data delivery.
Role Responsibilities
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. 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. 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. 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. 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. 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 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. 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). 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. 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.
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. 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. 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. 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. 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. 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 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. 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). 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. 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.