Contract Python Data Engineer

Quant Capital
London
10 months ago
Applications closed

Related Jobs

View all jobs

Data Architect (Insurance Domain)

Data Engineer - Burton-On-Trent

Data Engineer - Burton-On-Trent...

AWS Data Engineer

Graduate Data Engineer

Google Cloud Data Engineer

Python Data Engineer – Hedge Fund

Contract £1200 per day Outside IR35

Immediate Start



Quant Capital is urgently looking for a Contract Python Data Developer to join our high profile client.


Our client is a well known Systematic Trading Hedge Fund. They like technology especially the opensource variety as well as scalability and robust performance (much like their track record). They currently run around £2 billion in liquid capital.


This is an environment of google or a startup where tech is number 1 the firm is known globally for its attitudes and rigour more importantly, you will be surrounded by smart people deeply interested in teaching what they know, and in learning from you.


The environment is that of Facebook or Google, relaxed open with time to think and make the right decisions. The atmosphere is calm and relaxed with an open dress code. This is a role for techies, those who are motivated by the sharp end of technology and the possibility of making serious money doing something you are passionate about.


Day to Day the Python Data Engineer will:

Support and monitor the end-to-end lifecycle, including fixing errors and building out further functionality.

Assist ingestion of external data that will result in seamless integration of internal and external data sources.

Independently manage a code repository, documentation, and workflow from multiple teams and sources.

Communicate effectively with consumers, and external data providers to understand data formats and transformations.


The Python Data Developer Must have:

  • 2:1 Computer Science, Maths, Physics or Chemistry degree from a Red Brick UK or EU University
  • 15 years Experience in a Fund or Bank
  • Strong AWS Experience
  • Derivatives experience
  • Experience of Market Data Flows
  • Python
  • Airflow
  • Bloomberg
  • Must have experience in Trading or Investment management
  • An Understanding of computing fundamentals, object orientated programming, threading, concurrency and distributed systems




My client is based in Central London Hybrid.

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Neurodiversity in Data Science Careers: Turning Different Thinking into a Superpower

Data science is all about turning messy, real-world information into decisions, products & insights. It sits at the crossroads of maths, coding, business & communication – which means it needs people who see patterns, ask unusual questions & challenge assumptions. That makes data science a natural fit for many neurodivergent people, including those with ADHD, autism & dyslexia. If you’re neurodivergent & thinking about a data science career, you might have heard comments like “you’re too distracted for complex analysis”, “too literal for stakeholder work” or “too disorganised for large projects”. In reality, the same traits that can make traditional environments difficult often line up beautifully with data science work. This guide is written for data science job seekers in the UK. We’ll explore: What neurodiversity means in a data science context How ADHD, autism & dyslexia strengths map to common data science roles Practical workplace adjustments you can request under UK law How to talk about your neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in data science – & how to turn “different thinking” into a real career advantage.

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.