Contract Python Data Engineer

Quant Capital
London
1 year ago
Applications closed

Related Jobs

View all jobs

Senior Data Engineer (Distributed Data Processing)

Senior Python/Pandas FX Data Engineer (Contract)

Lead Data Engineer

Data Engineer

Snowflake & DBT Data Engineers

Data Engineer | Databricks & Python | 24-Month Contract

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.

Data Science Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Thinking about switching into data science in your 30s, 40s or 50s? You’re far from alone. Across the UK, businesses are investing in data science talent to turn data into insight, support better decisions and unlock competitive advantage. But with all the hype about machine learning, Python, AI and data unicorns, it can be hard to separate real opportunities from noise. This article gives you a practical, UK-focused reality check on data science careers for mid-life career switchers — what roles really exist, what skills employers really hire for, how long retraining typically takes, what UK recruiters actually look for and how to craft a compelling career pivot story. Whether you come from finance, marketing, operations, research, project management or another field entirely, there are meaningful pathways into data science — and age itself is not the barrier many people fear.

How to Write a Data Science Job Ad That Attracts the Right People

Data science plays a critical role in how organisations across the UK make decisions, build products and gain competitive advantage. From forecasting and personalisation to risk modelling and experimentation, data scientists help translate data into insight and action. Yet many employers struggle to attract the right data science candidates. Job adverts often generate high volumes of applications, but few applicants have the mix of analytical skill, business understanding and communication ability the role actually requires. At the same time, experienced data scientists skip over adverts that feel vague, inflated or misaligned with real data science work. In most cases, the issue is not a lack of talent — it is the quality and clarity of the job advert. Data scientists are analytical, sceptical of hype and highly selective. A poorly written job ad signals unclear expectations and immature data practices. A well-written one signals credibility, focus and serious intent. This guide explains how to write a data science job ad that attracts the right people, improves applicant quality and positions your organisation as a strong data employer.

Maths for Data Science Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are applying for data science jobs in the UK, the maths can feel like a moving target. Job descriptions say “strong statistical knowledge” or “solid ML fundamentals” but they rarely tell you which topics you will actually use day to day. Here’s the truth: most UK data science roles do not require advanced pure maths. What they do require is confidence with a tight set of practical topics that come up repeatedly in modelling, experimentation, forecasting, evaluation, stakeholder comms & decision-making. This guide focuses on the only maths most data scientists keep using: Statistics for decision making (confidence intervals, hypothesis tests, power, uncertainty) Probability for real-world data (base rates, noise, sampling, Bayesian intuition) Linear algebra essentials (vectors, matrices, projections, PCA intuition) Calculus & gradients (enough to understand optimisation & backprop) Optimisation & model evaluation (loss functions, cross-validation, metrics, thresholds) You’ll also get a 6-week plan, portfolio projects & a resources section you can follow without getting pulled into unnecessary theory.