Python Software Engineer (Data & Research Platforms)

TL;DR

Senior Python Software Engineer (Data & Research Platforms): Designing and building distributed data and research platforms that underpin systematic investment research with an accent on large-scale data processing, distributed systems, and reproducible workflows. Focus on optimizing data pipelines, improving system performance, and translating quantitative research requirements into robust engineering solutions.

Location: Hybrid in London

Salary: £250,000 Base + Bonus

Company

A boutique prop trading firm focused on systematic investment research with a technology-first culture and emphasis on engineering quality, scalability, and reproducibility.

What you will do

• Design and develop Python-based data and research platforms for large-scale analysis.
• Build and optimize distributed data pipelines to ingest, clean, transform, and store financial and alternative data.
• Develop frameworks and libraries that enable reproducible, scalable research workflows.
• Work closely with quantitative researchers and data teams to translate requirements into engineering solutions.
• Improve system performance, reliability, and scalability across research infrastructure.

Requirements

• Degree in Computer Science or a STEM discipline.
• Strong experience as a Python Software Engineer or in a similar position.
• Strong experience with Python for data engineering and research tooling.
• Familiarity with distributed systems and large-scale data processing.
• Solid understanding of modern software development practices (version control, testing, CI/CD).
• Excellent communication skills and ability to work closely with researchers.

Nice to have

• Experience with Kubernetes and Docker.

Culture & Benefits

• A core engineering role with direct impact on quantitative research productivity.
• Access to modern data technologies and distributed systems.
• Highly competitive compensation, bonus structure, and comprehensive benefits.
• A collaborative, research-driven environment with strong engineering ownership.
• Clear career progression and exposure to a wide range of data and research technologies.
• Strong focus on work-life balance and long-term sustainability.