A leading global investment firm is seeking a talented KDB+ Engineer to join its high-performance technology team in London. This is an opportunity to work at the heart of a cutting-edge trading environment, building and optimising the real-time data platforms that power systematic trading, quantitative research, and investment decision-making across global markets.
You'll work alongside world-class engineers, quantitative researchers, and traders, helping to develop highly scalable KDB+/q solutions that process vast amounts of market data with a focus on performance, reliability, and innovation.
This role is ideal for someone who enjoys solving complex technical challenges, working in a fast-paced environment, and having a direct impact on the success of a sophisticated trading business.
What You'll Be Doing
- Designing, building, and enhancing KDB+/q applications that underpin real-time trading and research systems
- Developing and maintaining critical market data infrastructure across trading, analytics, risk, and compliance functions
- Creating APIs, schemas, and data models that support trading platforms, quantitative research workflows, and simulation environments
- Optimising system performance, scalability, resilience, and latency across large-scale data platforms
- Partnering closely with traders, quantitative researchers, and software engineers to deliver high-impact technology solutions
- Investigating production issues and ensuring the robustness of business-critical trading applications
- Driving continuous improvements to platform architecture, tooling, and engineering standards
What We're Looking For
- Strong commercial experience with KDB+/q
- Proficiency in Python and its application within data-intensive environments
- Solid Linux/Unix systems knowledge
- Experience working with financial market data and real-time trading systems
- Strong problem-solving abilities and a passion for building high-performance systems
- Excellent communication skills with the ability to collaborate across technology and front-office teams
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