Contract Python Data Engineer

Quant Capital
London
1 year ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer - (Python, SQL, Machine Learning) - Robotics

Lead Data Engineer - Hadoop - Spark - Python

Technical Data Engineer / Analyst

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.

Careers

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

Jobs

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.

Education

The Skills Gap in Data Science Jobs: What Universities Aren’t Teaching

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.