Senior Data Engineer Job Details | JLR

Jaguar Land Rover
Coventry
4 days ago
Applications closed

Related Jobs

View all jobs

Senior Data Engineer, SQL, RDBMS, AWS, Python, Mainly Remote

Data Engineer

Senior Data Analyst

Senior Data Scientist Research Engineer

Senior RF Data Scientist / Research Engineer

Principal Data Engineer (Azure, PySpark, Databricks)

REQ ID: 129386
JOB TITLE: Senior Data Engineer
SALARY: £50,100 - £60,000
POSTING START DATE: 21/07/2025
POSTING END DATE: 04/08/2025
LOCATION: Coventry - Hybrid

In a commercial role at JLR, you can reimagine the future of modern luxury. In teams focused on extraordinary customer experience, sustainability and forward-thinking. You’ll work alongside strategically-minded problem-solvers supporting the transformation of our iconic house of brands – Range Rover, Defender, Discovery, and Jaguar – and our heritage-rich JLR Classic range. Becoming a proud creator of the exceptional starts here.

The automotive industry is in the midst of a significant transformation driven by innovations in car connectivity, data-driven advancements, and the ongoing digital evolution of vehicles. Against this backdrop, we have an exciting opportunity within Customer Care Quality to transform the quality of our products through the use of AI & data science, thereby enabling a modern luxury customer experience.

As a Senior Data Engineer in CCQ, you’ll play an important role within a dynamic team that is helping to innovate how we can best harness the vast amount of data and leverage AI & data science to increase the speed of issue detection, the depth of issue understanding, and the pace of issue resolution.

WHAT TO EXPECT

In this role, no two tasks are the same. With lots of projects and relationships to build with people across the business and beyond, it’s a challenge that will help your career grow within an iconic organisation. Here’s what to expect:

  • Use AI and data science to identify, analyse, and anticipate customer quality issues from diverse sources such as warranty, manufacturing, and connected car data
  • Join a pioneering team within Customer Care Quality (CCQ) to transform vehicle quality using AI and data science, enhancing the modern luxury customer experience
  • Work with diverse datasets to detect, understand, and resolve customer issues proactively
  • Play a key role in accelerating issue detection, deepening insights, and speeding up resolution through advanced data engineering and analytics
  • Partner with analytics experts and cross-functional teams to deliver impactful solutions that improve product quality and customer satisfaction
  • Ideal for a self-motivated problem-solver with a passion for continuous learning and adaptability in a fast-evolving automotive landscape

WHAT YOU’LL NEED

Along with your ambition to achieve the exceptional, there are several skills that you’ll need to have to help you succeed here, including:

  • Experience in data engineering or data architecture
  • Experience in building and maintaining data pipelines
  • Experience with at least one major Cloud-based platform (GCP, AWS, Azure)
  • Understanding of cloud-native practices and containerisation
  • Strong understanding of at least one programming language (e.g. Python) in a data engineering context

BENEFITS

This role is rewarding in more ways than one. On top of our core offering, you’ll do extraordinary work with amazing people. In addition, you can expect a wide range of benefits:


•Discounted car purchase (open to family members, too)
•A 52 week maternity leave policy and a 4 week paternity leave policy. Other parental leave policies are available.
•A competitive pension
•A JLR company performance-related bonus
•An employee learning scheme providing funding for; education, training and other activities which support the development of personal skills and promote lifelong learning.
•Access to open, employee-led support and social networks
•Comprehensive Life Assurance and Income Protection policies
•Flexible working*

*Flexible working is offered for specific roles dependant on responsibilities. Please speak to the hiring team for details.

Creating Modern Luxury requires a modern approach to work. At JLR, hybrid working is a voluntary, non-contractual arrangement providing employees more choice and flexibility around how, when and where they work. Some roles require more on-site work, but details of this can be discussed with the hiring manager during the interview stage.

We work hard to nurture a culture that is inclusive and welcoming to all. We understand candidates may require reasonable adjustments during the recruitment process. Please discuss these with your recruiter so we can accommodate your needs.

Applicants from all backgrounds are welcome. If you’re unsure that you meet the full criteria of a role – but you're interested in where it could take you – we still encourage you to apply. We believe in people's ability to grow and develop within their role – it’s what makes living the exceptional with soul possible.

JLR is committed to equal opportunity for all.


#J-18808-Ljbffr

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.

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

Are you considering a career change into machine learning in your 30s, 40s or 50s? You’re not alone. In the UK, organisations across industries such as finance, healthcare, retail, government & technology are investing in machine learning to improve decisions, automate processes & unlock new insights. But with all the hype, it can be hard to tell which roles are real job opportunities and which are just buzzwords. This article gives you a practical, UK-focused reality check: which machine learning roles truly exist, what skills employers really hire for, how long retraining realistically takes, how to position your experience and whether age matters in your favour or not. Whether you come from analytics, engineering, operations, research, compliance or business strategy, there is a credible route into machine learning if you approach it strategically.

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.

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

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.