Staff Data Engineer, Market Data

Coinbase, Inc.
Lansing, MI, United States
13 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Compensation
$207,485.0 - $244,100.0
Working hours
Regular working hours

Tech stack

Java (Programming Language) Algorithmic Trading C++ (Programming Language) Low Latency

Job description

Coinbase is building the future of institutional trading as part of the Everything Exchange, powering the systems that let the world’s largest financial institutions trade across markets with speed, depth, and trust. As a Market Data Engineer on the Markets team, you’ll architect, build and own the systems that generate, capture, normalize, and distribute real-time market data across Coinbase at low latency - the ticker plant and distribution backbone of a unified trading platform - while leading a lean, high-impact team. It’s a rare chance to architect market data infrastructure from the ground up, with the ownership of a startup and the reach of Coinbase.

What you’ll do:

  • Build and operate market data components: feed handlers, normalization, distribution, and venue connectivity.
  • Design low-latency, high-throughput systems for real-time market data used by trading systems.
  • Contribute to reliability and performance, participating in observability, on-call, and incident response.
  • Write high-quality, well-tested code and help raise the quality bar on a lean team.
  • Partner with engineers, product, and cross-functional stakeholders to deliver market data capabilities.

Requirements

  • 5+ years of backend engineering, with experience building and maintaining production low-latency systems.
  • Hands-on experience with market data systems (feed handlers, normalization, or distribution).
  • Proficiency in low-latency Java (or C++) and high-throughput messaging (Aeron, SBE, or similar).
  • Familiarity with venue/exchange connectivity and market data protocols (FIX, ITCH/OUCH, multicast).
  • Track record delivering features end-to-end and operating what you build.
  • Utilizes generative AI responsibly, maintaining human oversight to deliver business-ready outputs and drive measurable improvements in workflow efficiency, cost, and quality.

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