Data Engineering Manager

What you'll do

• Own and improve market data pipelines, including exchange-feed integration, sequencing, validation, replay, recovery, and near-real-time delivery.
• Design, maintain, and troubleshoot KDB+/Q real-time and historical data platforms, including schemas, performance, retention, and production issues.
• Write production code, lead technical reviews, support production operations, and guide the platform’s evolution for human and machine-driven data use.

What they ask for

• At least 7 years of experience in data engineering, market data infrastructure, or a closely related area.
• Current hands-on production coding experience and at least 3 years leading engineers while technically involved.
• Strong KDB+/Q and production Python experience, including complex Q, tick architecture, query tuning, and maintainable systems-level code.
• Experience building low-latency decoders for real exchange protocols; strong understanding of multicast, packet capture, sequencing, and gap detection.

Nice to have

• Background in high-frequency trading, market making, proprietary trading, or another latency-sensitive environment.
• C or C++ experience, kernel-bypass or high-performance networking, streaming platforms, or binary market data encoding standards.

Pay

$180,000 - $250,000 USD base salary

Tools

KDB+ / Q, Python, C / C++, Linux, Docker, Git / CI-CD, FIX, SBE, perf, strace, tcpdump, and numactl

AI focus

Prepare the data platform for AI-driven tools, models, and agents through clean structure, metadata, lineage, context, and appropriate access patterns; develop a practical point of view on its evolution for machine-driven use.