Senior Python Engineer - Systematic Trading & Analytics

Selby Jennings; Greater London; Vor Ort; GBP 90.000 - 150.000; Vollzeit

Zusammenfassung

Selby Jennings is seeking an experienced Python engineer to design, develop and maintain production-grade Python applications in a financial analytics context. You will build scalable infrastructure for large datasets, partner with quantitative researchers and investment teams, and drive reliability, performance and architecture improvements.

You'll own projects through the full software lifecycle, contribute engineering leadership, and promote best practices across the team.

Qualifikationen

• Strong software engineering background with significant commercial experience, ideally gained within a hedge fund, asset manager, proprietary trading firm, investment bank or financial technology environment.
• Expert-level Python development skills with a proven track record of building complex, large-scale production systems.
• Experience developing data-intensive platforms, analytics infrastructure, market data, pricing, research or quantitative technology applications.
• Strong understanding of software architecture, system design and engineering best practices.
• Exposure to options, derivatives, volatility markets or quantitative investment environments, with the ability to engage effectively with researchers, traders, portfolio managers and quantitative teams.
• Experience building technology that supports financial analytics, systematic trading workflows or quantitative research processes would be highly beneficial.
• Excellent communication skills and the ability to work effectively with both technical and non-technical stakeholders.

Aufgaben

• Design, develop and maintain production-grade Python applications.
• Build scalable infrastructure supporting large datasets and analytical workloads.
• Develop software used for financial analytics, research and investment decision-making.
• Partner closely with quantitative researchers and investment teams to deliver technical solutions.
• Drive improvements in system architecture, reliability, scalability and performance.
• Own projects throughout the full software development lifecycle.
• Contribute ideas, technical leadership and engineering best practices across the team.

Kenntnisse

Python

Software engineering

Data analytics

Large-scale systems

Financial tech

Cloud infrastructure

Stakeholder communication

Jobbeschreibung

• Design, develop and maintain production-grade Python applications.
• Build scalable infrastructure supporting large datasets and analytical workloads.
• Develop software used for financial analytics, research and investment decision-making.
• Partner closely with quantitative researchers and investment teams to deliver technical solutions.
• Drive improvements in system architecture, reliability, scalability and performance.
• Own projects throughout the full software development lifecycle.
• Contribute ideas, technical leadership and engineering best practices across the team.

Requirements

• Strong software engineering background with significant commercial experience, ideally gained within a hedge fund, asset manager, proprietary trading firm, investment bank or financial technology environment.
• Expert-level Python development skills with a proven track record of building complex, large-scale production systems.
• Experience developing data-intensive platforms, analytics infrastructure, market data, pricing, research or quantitative technology applications.
• Strong understanding of software architecture, system design and engineering best practices.
• Exposure to options, derivatives, volatility markets or quantitative investment environments, with the ability to engage effectively with researchers, traders, portfolio managers and quantitative teams.
• Experience building technology that supports financial analytics, systematic trading workflows or quantitative research processes would be highly beneficial.
• Excellent communication skills and the ability to work effectively with both technical and non-technical stakeholders.