Python Data Developer - Risk

I’m working with a leading quantitative investment firm that’s investing heavily in the modernisation of its risk and analytics platform.

This is an opportunity to join a highly technical engineering team responsible for building the next generation of risk infrastructure used across the business. The team is replacing legacy processes with scalable, high-performance data platforms, enabling faster analytics, real-time decision making and more sophisticated tooling for front-office stakeholders.

This is a hands-on engineering role with a strong focus on software development, data engineering and platform design. While there is some exposure to supporting existing systems, the emphasis is firmly on building modern solutions that will underpin the firm’s risk technology for years to come.

What You’ll Be Doing

• Design and develop Python-based applications that support risk analytics and reporting.
• Build and maintain ETL pipelines to ingest, transform and enrich large financial datasets.
• Design efficient data models for high-performance analytical databases.
• Contribute to the migration from legacy technologies to a modern data platform.
• Optimise reporting and analytics for both batch and real-time workloads.
• Work closely with Risk Managers and engineering teams to develop tools that solve complex business problems.
• Help shape the future architecture of the firm’s risk technology estate.

• Strong software engineering fundamentals with commercial development experience.
• Experience building backend applications in Python or another modern programming language.
• Exposure to ETL pipelines, data transformation or data engineering.
• Strong SQL and database design skills.
• Experience working with analytical or OLAP databases such as ClickHouse, Snowflake, DuckDB or similar is highly desirable.
• Understanding of software testing, CI/CD and engineering best practices.
• Excellent communication skills and a collaborative approach to working with technical and non-technical stakeholders.
• Financial services experience is beneficial but not essential. Candidates from other engineering environments with strong transferable skills are encouraged to apply., * Experience working with risk systems or financial data.
• Knowledge of Pandas, Polars or similar data frame libraries.
• Experience migrating legacy platforms or modernising existing systems.
• Exposure to real-time data processing or analytics platforms.

• Join a highly regarded quantitative investment firm with a genuine engineering culture.
• Work on greenfield platform development rather than maintaining legacy systems.
• Help build technology that enables real-time analytics across the business.
• Collaborate with experienced engineers in a technically challenging environment.
• Influence the design of a modern data platform from an early stage.
• Competitive compensation, performance bonus and excellent long-term career progression.