Data Science Engineer

Expleo Group
Warwick
6 days ago
Create job alert

Expleo is seeking a highly capable Data Science Engineer to support our prestigious automotive customer based in Gaydon. This is an exciting opportunity to play a critical role in shaping data solutions within advanced manufacturing engineering environments.

You will be responsible for delivering meaningful, actionable insights from operational data, developing automation solutions, and optimising reporting capabilities. This role is ideal for someone who thrives on ownership, collaboration, and driving measurable improvements.

Location: Gaydon, Warwickshire (on-site with travel to other UK sites as required)

Contract Basis

Key Duties & Responsibilities

  • Engage with stakeholders and management to identify opportunities, improvements, and gaps in current reporting.
  • Identify, clean and transform operational data to create actionable insights and dashboards.
  • Automate data extraction and transformation processes.
  • Identify, develop and maintain Power App solutions for gaps in current data capture.
  • Undertake any other work as directed by the line manager in connection with the role.

Knowledge, Skills and Experience

Hard Skills:

  • Proven experience of developing dashboards and reporting capabilities with Tableau.
  • Ability to visually display data in a meaningful way that helps end users understand business performance and take appropriate actions.
  • Understanding of data modelling and relational database structures.
  • Experience using SQL to extract and transform data.
  • Experience automating data extraction and transformation processes.
  • Experience developing and maintaining Power Apps and Power Automate solutions.
  • Possess a valid driving licence, required to travel to different UK sites when required.

Soft Skills:

  • Ability to work independently and proactively, taking full ownership and responsibility for own work.
  • A team-focused mindset, considering wider team needs beyond individual project level.
  • Strong interpersonal and communication skills, with the ability to manage relationships and communicate effectively at all levels.
  • Good influencing skills.
  • Good problem-solving skills.

Hard Skills:

  • Experience using the Enterprise Data Warehouse to extract, transform and load data.
  • Experience with Python.

Soft Skills:

  • Relevant Data apprenticeship / Degree or equivalent experience preferred.

đźš« Please note: Sponsorship is NOT available for this position. Applicants must have the right to work in the UK.


#J-18808-Ljbffr

Related Jobs

View all jobs

Data Science Engineer Global Digital Media/MarTech

Data Science Engineer

Data Science Engineer Intern — Summer 2026

Data Science Engineer: Growth & Revenue Modeling

Data Science Engineer – High-Performance Vehicle AI

Data Science Engineering Manager – Audit (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.

New Data Science Employers to Watch in 2026: UK and International Companies Leading Analytics and AI Innovation

Data science has emerged as one of the most transformative forces across industries, turning raw information into actionable insights, predictive models, and AI-powered solutions. In 2026, the UK is witnessing a surge in organisations where data science is not just a support function but the core of their products and services. For professionals exploring opportunities on www.DataScience-Jobs.co.uk , identifying these employers early can provide a competitive advantage in a market with high demand for advanced analytics and machine learning expertise. This article highlights new and high-growth data science employers to watch in 2026, focusing on UK startups, scale-ups, and global firms expanding their data science operations locally. All of the companies included have recently raised investment, won high-profile contracts, or significantly scaled their analytics teams.

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.

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.