Hunter Bond
Risk Data Pipeline Software Engineer (Python / C++) : £200k+
How your CV stacks up
Upload your CV to see how well it fits this job role
?%
About the Firm
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.
Reasons to use Rodeo
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
It searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
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
Get help with your application
Your very own career expert that helps elevate your application to the next level.
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
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
Skills
Location