Job Description
Our client is a global financial services and market infrastructure business operating across commodities, energy and financial markets. They provide liquidity, execution, clearing and risk solutions to a broad institutional client base including banks, hedge funds, asset managers, traders and producers.
With an international footprint and significant market presence across exchange-traded and OTC markets, technology plays a critical role in enabling the scale, reliability and sophistication of their services.
The Opportunity
This role sits within a business-facing Risk Technology team focused on building and enhancing strategic risk systems and analytics platforms used across multiple areas of the business.
The successful candidate will join a team responsible for developing scalable risk engines and improving complex calculation, reporting and data-processing workflows across areas such as:
- Market Risk
- Counterparty Risk
- Clearing Risk
- Operational Risk
- Exposure and VaR/CVaR calculations
This is a highly collaborative role sitting close to both technology and business stakeholders, offering strong exposure to quantitative risk processes, large-scale data engineering challenges and modern cloud-based engineering practices.
Key Responsibilities
- Develop and enhance strategic risk engine applications and supporting infrastructure
- Build scalable numerical-processing systems and high-volume data workflows
- Improve automation, reporting and operational efficiency across risk platforms
- Integrate and standardise data across internal and vendor systems
- Work closely with Risk, Platform Engineering, Application Support and wider technology teams
- Contribute to architecture discussions, testing strategy and engineering best practices
- Identify opportunities for process improvement and platform optimisation
- Work with modern AI-assisted development tooling where appropriate
Technical Environment
- Python
- Pandas / NumPy / Polars / PySpark
- Async processing / coroutines
- AWS cloud technologies
- Databricks
- Docker
- Relational and non-relational databases
- CI/CD and automated testing
- Agile/Scrum delivery environments
Ideal Background
- Strong Python engineering experience with focus on scalable backend or data-intensive systems
- Experience building applications involving complex calculations or large-scale processing
- Exposure to cloud-native technologies and distributed systems
- Strong understanding of software engineering best practices, testing and automation
- Experience operating within regulated or financial services environments is beneficial
- Strong communication and stakeholder engagement skills
The Environment
The team are looking for engineers who are collaborative, technically curious and comfortable operating within a fast-paced environment. The role offers strong long-term growth potential within a modernising technology function supporting commercially critical business areas.
Contact Ciara Clarke at Harrington Starr for a confidential discussion on this role.