Risk Data Pipeline Software Engineer (Python / C++) : £200k+

Our client is a highly successful, technology-driven quantitative investment firm that develops systematic trading strategies across global markets. They are seeking a Risk Data Pipeline Software Engineer to join a high-performing engineering team responsible for building the data infrastructure that underpins real-time and end-of-day risk across the firm. This is an opportunity to work at the intersection of quantitative research, trading, and technology, designing highly scalable data pipelines that deliver accurate, low-latency risk data to portfolio managers, researchers, and risk teams. The Role You'll play a key role in designing, building, and maintaining robust data pipelines that process large volumes of market, trading, and portfolio data. Working closely with quantitative developers, risk managers, and infrastructure engineers, you'll help ensure the firm's risk systems remain accurate, resilient, and performant. The environment is collaborative, fast-paced, and engineering-led, with significant ownership and the opportunity to influence architecture across the firm's technology stack. Responsibilities Design, develop, and optimise scalable risk data pipelines using Python and/or modern C++ Build high-performance ETL and streaming solutions for market, reference, position, and risk data Develop robust validation and monitoring frameworks to ensure data quality and integrity Integrate with real-time market data feeds, trading systems, and risk engines Optimise data storage, processing, and distribution for low-latency analytical workloads Collaborate with quantitative researchers, portfolio managers, and risk teams to understand evolving requirements Improve automation, observability, and operational resilience across production systems Contribute to architectural decisions and engineering best practices Requirements Strong commercial experience developing production systems in Python , C++ , or both Experience building large-scale data pipelines or distributed data processing platforms Strong understanding of data structures, algorithms, and software engineering principles Experience with SQL and modern database technologies Familiarity with messaging technologies, streaming platforms, or event-driven architectures Experience working on Linux-based production environments Excellent problem-solving skills with strong attention to detail Desirable Experience Experience within quantitative finance, hedge funds, investment banking, or electronic trading Knowledge of risk systems, market data, pricing, or portfolio analytics Experience with distributed computing frameworks Cloud infrastructure experience (AWS, Azure, or GCP) Containerisation and orchestration technologies such as Docker and Kubernetes CI/CD and infrastructure automation