Front-Office Risk Tech Engineer - Python

Paragon Alpha - Hedge Fund Talent Business; Greater London; On-site; GBP 85,000 - 135,000; Full time

Job summary

Paragon Alpha - Hedge Fund Talent Business seeks a RiskTech Engineer to design and build high-performance Python-based risk applications for front-office users. You will work with Portfolio Managers, Quant Researchers and Risk Managers to transform quantitative research into scalable production systems, with cloud-native architecture.

The role involves delivering risk analytics, building data pipelines, and deploying services that support risk and quantitative research across the investment

Qualifications

• 7+ years' software engineering experience in financial services.
• Strong Python and/or C# development experience.
• Experience building scalable, production-grade applications.
• Strong SQL and database knowledge.
• Experience with large datasets and distributed data processing.
• Excellent problem solving skills and ability to work independently.

Responsibilities

• Design, build and maintain scalable Python-based risk applications.
• Develop services and interfaces delivering risk analytics to front-office users.
• Build and optimise large-scale data processing pipelines.
• Deploy and support cloud-native applications and infrastructure.
• Collaborate with Risk, Quant Research and Portfolio Management to deliver new functionality.
• Drive projects from design through production deployment.

Skills

Python

C#

SQL

problem solving

distributed data processing

data analysis

Tools

AWS

Docker

Kubernetes

Job description

Paragon Alpha - Hedge Fund Talent Business seeks a RiskTech Engineer to design and build high-performance Python-based risk applications for front-office users. You will work with Portfolio Managers, Quant Researchers and Risk Managers to transform quantitative research into scalable production systems, with cloud-native architecture.

The role involves delivering risk analytics, building data pipelines, and deploying services that support risk and quantitative research across the investment