Python Lead Software Engineer - Rates Live Risk & P&L
Salary not stated · Compare with UK Risk Analyst pay →
Description
You will join a front-office engineering team that builds and operates core Rates trading tooling where correctness, resilience, and latency matter every day. The environment is fast-moving and highly collaborative, with strong expectations for production ownership, rapid iteration, and high-quality delivery.
Job Responsibilities
- Build and enhance Python services and applications that power live Rates risk and P&L, with a strong focus on low latency and predictable performance.
- Partner directly with traders and risk managers to turn time-sensitive requirements into reliable, production-ready solutions.
- Own production services end-to-end, including releases, monitoring, incident response, and root-cause analysis.
- Troubleshoot issues across distributed components, data flows, and runtime environments; drive fixes that reduce recurrence.
- Improve DevOps and operational readiness, including CI/CD, environment management, dependency management, and automation.
Maintain strong engineering standards through code reviews, testing discipline, performance profiling, and clear documentation/runbooks.
Required qualifications, capabilities, and skills
- Strong Python development skills, including writing production-quality code with solid testing and packaging practices.
- Experience building and operating production services, including production support and incident-driven troubleshooting.
- Practical SDLC discipline across design, implementation, testing, deployment, and release management.
- Experience with CI/CD and observability (monitoring, alerting, logs/metrics) to keep services stable and measurable.
- Ability to work closely with front-office stakeholders and deliver effectively when priorities shift.
- Strong debugging skills and comfort navigating multi-component systems.
Preferred qualifications, capabilities, and skills
Financial markets background, especially Rates trading, risk, or P&L concepts.
- Exposure to Deephaven, including installation and dependencies (for example GKP, Java interoperability, and runtime operations).
- Low-latency/performance engineering experience (profiling, concurrency, and latency measurement).
- Understanding of UI programming and interactive workflows used by traders.
- Strong DevOps mindset (automation, environment consistency, and operational ownership).
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