Don't miss out on your perfect opportunity. Create personalised job alerts and be the first to know about new openings.
Save Time and Effort
Stop endlessly searching. We'll send you relevant jobs directly to your inbox.
Targeted Job Matching
Receive alerts for jobs that match your skills, experience, and career goals.
Instant Notifications
Be the first to apply with instant email alerts for new job postings.
Featured Jobs
Data Governance Analyst
As a Data Governance Analyst, you will support the Data Governance Manager in implementing and maintaining the organisation’s data governance framework. Your role will involve ensuring data quality, consistency, and compliance across various data domains. You will work closely with data owners, data stewards, the Records & Retention Officer, and IT teams to enforce data governance policies and procedures and...
Pertemps Thames Water
Reading
Data Engineer
We’re looking for someone with strong Informatica expertise. The core requirements are: Hands‑on Informatica experience (IICS / ETL design and support) – this is critical SC clearance (or very close to obtaining it) Strong SQL / data engineering background, ideally in Azure‑based environments Nice to have / optional skills (not essential, but beneficial): Experience with Microsoft Fabric (e.g. Data Factory,...
Qualient Technology Solutions UK Limited
London
Senior Data Engineer
Senior Data Engineer – (Tick data, Time-Series; kdb+ / Q ) 3-6 months initially. London 3 days onsite Are you a Data Engineer with a background in systematic trading who has worked with granular tick market data? Have you built pipelines to allow tick data to be ingested into a time series tech stack utilising kdb+ and Q? If so...
Certain Advantage
South Bank
Data Engineer
We are Data Services, our mission is to unlock the value of data by delivering high-quality, reliable, and secure data services that are accessible, understandable, and actionable. We continuously evolve our offerings, leveraging modern cloud-based technologies, and fostering strong partnerships to help our colleagues in the Bank navigate the complexities of a data-driven world and achieve their strategic objectives. Active...
Peregrine
London
Senior Data Engineer
Your new company An established and fast‑growing technology organisation is on a mission to transform digital connectivity across the UK. With a focus on building and operating high‑speed fibre networks, the business is committed to delivering world‑class broadband services to communities and supporting a data‑driven future. You'll be joining a forward‑thinking environment that values innovation, collaboration, and continuous improvement. Your...
Hays Technology
Abingdon
Data Engineer
Data Engineer | Outside IR35 | £450 - £500 | 6 months | Hybrid London We’re supporting a company who are looking for a Data Engineer to build and enhance the data processing capabilities within their Databricks environment. You’ll be responsible for developing the code that drives their data pipelines, using Python, Spark, and Databricks Workflows to deliver new platform...
Data engineering is at the heart of the digital economy, transforming raw data into actionable insights, powering analytics, AI systems, and cloud infrastructure. As the UK and global markets continue to invest heavily in data platforms, pipelines, and real-time analytics, demand for skilled data engineers is growing rapidly.
For professionals exploring opportunities on www.DataEngineeringJobs.co.uk
, the critical question is: which companies are expanding, hiring, and shaping the future of data-driven business? This article highlights new data engineering employers to watch in 2026, including UK startups, scale-ups, and international firms expanding in the UK.
If you’re aiming for a career in data engineering, it can feel like you’re staring at a never-ending list of tools and technologies — SQL, Python, Spark, Kafka, Airflow, dbt, Snowflake, Redshift, Terraform, Kubernetes, and the list goes on.
Scroll job boards and LinkedIn, and it’s easy to conclude that unless you have experience with every modern tool in the data stack, you won’t even get a callback.
Here’s the honest truth most data engineering hiring managers will quietly agree with:
👉 They don’t hire you because you know every tool — they hire you because you can solve real data problems with the tools you know.
Tools matter. But only in service of outcomes. Jobs are won by candidates who know why a technology is used, when to use it, and how to explain their decisions.
So how many data engineering tools do you actually need to know to get a job? For most job seekers, the answer is far fewer than you think — but you do need them in the right combination and order.
This article breaks down what employers really expect, which tools are core, which are role-specific, and how to focus your learning so you look capable and employable rather than overwhelmed.
If you’re applying for data engineering jobs in the UK, the first thing to understand is this:
Hiring managers don’t read every word of your CV. They scan it. They look for signals of relevance, credibility, delivery and collaboration — and if they don’t see the right signals quickly, your application may never get a second look.
In data engineering, hiring managers are especially focused on whether you can build and operate reliable, scalable data systems, handle real-world data challenges and work effectively with analytics, BI, data science and engineering teams. This guide breaks down exactly what they look at first in your application — and how to shape your CV, portfolio and cover letter so you stand out.
Data engineering has quietly become one of the most critical roles in the modern technology stack. While data science and AI often receive the spotlight, data engineers are the professionals who design, build and maintain the systems that make data usable at scale.
Across the UK, demand for data engineers continues to rise. Organisations in finance, retail, healthcare, government, media and technology all report difficulty hiring candidates with the right skills. Salaries remain strong, and experienced professionals are in short supply.
Yet despite this demand, many graduates with degrees in computer science, data science or related disciplines struggle to secure data engineering roles.
The reason is not academic ability. It is a persistent skills gap between university education and real-world data engineering work.
This article explores that gap in depth: what universities teach well, what they consistently miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data engineering.
Thinking about switching into data engineering in your 30s, 40s or 50s? You’re not alone. In the UK, companies of all sizes — from fintechs to government agencies, retailers to healthcare providers — are building data teams to turn vast amounts of information into insight and value. That means demand for data engineering talent remains strong, but there’s a gap between media hype and the real pathways available to mid-career professionals.
This guide gives you the straight UK reality check: which data engineering roles are genuinely open to career switchers, what skills employers actually look for, how long retraining really takes and how to position your experience for success.
Data engineering is the backbone of modern data-driven organisations. From analytics and machine learning to business intelligence and real-time platforms, data engineers build the pipelines, platforms and infrastructure that make data usable at scale.
Yet many employers struggle to attract the right data engineering candidates. Job adverts often generate high application volumes, but few applicants have the practical skills needed to build and maintain production-grade data systems. At the same time, experienced data engineers skip over adverts that feel vague, unrealistic or misaligned with real-world data engineering work.
In most cases, the issue is not a shortage of talent — it is the quality and clarity of the job advert.
Data engineers are pragmatic, technically rigorous and highly selective. A poorly written job ad signals immature data practices and unclear expectations. A well-written one signals strong engineering culture and serious intent.
This guide explains how to write a data engineering job ad that attracts the right people, improves applicant quality and positions your organisation as a credible data employer.
Find the perfect job? Subscribe to job alerts to stay informed about new opportunities.
Get DATA-ENGINEERING Job Alerts Directly to Your Inbox! Specify your desired role, and we'll send you email alerts whenever new DATA-ENGINEERING jobs matching your criteria are posted.
🍪 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.
:quality(80))
:quality(80))
:quality(80))
:quality(80))
:quality(80))
:quality(80))