Low Latency Market Data Engineer

About the role

Hytech, a management consulting firm focused on digital transformation for fintech and financial services, is building a high-performance market making operation and is looking for a founding member of its trading infrastructure team. As Low Latency Market Data Engineer, you will own the full data layer, from institutional feed ingestion to the composite real-time reference prices that power the quoting engine. This is a high-ownership, greenfield role with direct visibility into how the infrastructure drives trading performance.

Key responsibilities

• Design, build and maintain production-grade feed handlers for institutional market data sources and crypto exchange APIs, owning uptime, latency and data quality SLAs.
• Build and continuously improve a real-time composite pricing model with dynamic source weighting, outlier detection and automated failover logic.
• Profile and reduce end-to-end feed-to-application latency through kernel-level Linux tuning, CPU affinity, interrupt handling and NIC configuration.
• Implement automated feed health monitoring and alerting to detect stale prices, source outages and timestamp anomalies in real time.
• Work closely with the trading and infrastructure teams to turn pricing model requirements into robust feed infrastructure.

Required profile

• 5-8 years of experience in market data engineering within a live trading environment (HFT, market making or institutional prop trading).
• Hands-on production experience with institutional market data feeds such as LSEG/Refinitiv Elektron or equivalent, including feed handler development (not terminal usage).
• Fluent English and Mandarin to work with Mandarin-speaking stakeholders.

Required skills

• Strong Linux systems expertise, including CPU affinity, NUMA, kernel network stack tuning and latency profiling tools.
• C++ and/or Python for production feed handler development; knowledge of OTC market data structure (FX or commodities spot pricing) is essential.
• Experience building composite pricing models from multiple sources; familiarity with crypto exchange WebSocket feeds is a strong plus.