Powertrain Charging Test Data Engineer

Coventry
10 months ago
Applications closed

Our OEM Client based in Whitley, Coventry is searching for a Powertrain Charging Test Data Engineer to join their team, Inside IR35. This is a 12-month contract position initially until 31st March 2026, with the potential for further extensions.

Umbrella Pay Rate: £27.03 per hour.

This role sits within the Powertrain Charging Systems Team, in the Charging Validation & Verification organisational unit. The role will focus on delivering data from tests in support of design release activity or technology advancement of electric vehicle charging infrastructure compatibility. The main activity for this role as part of a team would be to prepare test facility or test parts with instrumentation which enables measurement of a wide range of charging system signals and variables, both on-board and external to the vehicle.

In addition, this role will support the collection of data in a wide range of environments such as in a test facility, on public roads and proving grounds. The key outcome of this role is to help create a modern luxury seamless and stress-free charging experience for our customers.

Skills Required:

Awareness of existing charging Standards (e.g. CCS / COMBO, DIN 70121 and ISO15118).
Experience with IATF16949 or ISO9001 standards and requirements.
A full UK driving license with less than 6 penalty points, no disqualification, 2 years accident-free record.
Experience Required:

Good communication and negotiation skills.
Strong organisational and planning skills.
Eagerness to learn about Electric Vehicle Charging Studying data and reporting of test data.
Natural problem-solver with structured approach to problem solving in a technical environment.
The ability to validate, prepare and read documentation.
Knowledge of Health and Safety processes.
Computer literate, including Microsoft Office competency to produce plans, presentations, graphs, process and Single Point Lesson (SPL) documents.
Experience Preferred:

Demonstrable software integration knowledge.
Vehicle Charging Systems and Applications experience.
Demonstrable electronic hardware design and test knowledge.
Six Sigma, Black Belt and Green Belt Training and certification.
Experience and certification for conducting testing on proving grounds.
Knowledge of instrument calibration processes.
Proficient in the use and application of a programming / scripting language (C/C++, python, Java, or similar).
Educated to Degree level in a Systems, Mechanical, Electrical/Electronic or related field or equivalent

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.

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.

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.