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Featured Jobs

£70,000 – £100,000 pa On-site Permanent

Senior Data Engineer

The Senior Data Engineer / Analytics Lead will establish and lead the data engineering and analytics capability within RSM's Forensic Technology team. Responsibilities include designing and building data pipelines, working directly with clients and regulators, mentoring junior staff, and setting technical standards. This greenfield role offers the opportunity to shape the function and deliver impactful forensic solutions.

RSM logo

RSM

London, United Kingdom

£100,000 – £150,000 pa Hybrid Permanent

EMEA Energy Industry Go-To-Market (GTM) Leader

This role involves leading the go-to-market strategy for Databricks in the energy sector across EMEA. Responsibilities include setting AI vision with top energy accounts, driving pipeline growth, and aligning cross-functional teams. The position requires deep industry expertise and a proven track record in strategic consulting and technology commercialization.

Databricks logo

Databricks

United Kingdom

£700 – £750 pd Hybrid Contract Clearance Required

Data Architect

As a Data Architect, you will lead the strategic integration of agentic AI and large language models across the enterprise, defining governance frameworks and advising senior stakeholders. You will collaborate with external AI providers, mentor senior architects, and ensure compliance with enterprise standards.

Experis logo

Experis

Croydon, London, United Kingdom

£45 ph Hybrid Contract Part-time Clearance Required

Technical Data Engineer

The role involves authoring, reviewing, and maintaining Aircraft Maintenance Manuals (AMM) and Troubleshooting Manuals (TSM) for Landing Gear systems. You will work within a transnational technical data environment, ensuring maintenance documentation accurately reflects aircraft configuration and meets regulatory requirements. Key responsibilities include managing source data, responding to customer queries, and driving continuous improvement in technical data processes.

Belcan logo

Belcan

Filton, Gloucestershire, United Kingdom

£40,000 – £60,000 pa On-site Permanent

Startup Hunter Account Executive, UKI

As a Startup Hunter Account Executive, you will focus on acquiring new accounts in the UK and Ireland, developing account execution strategies, and identifying new use cases. You will work closely with prospects to showcase the value of Databricks' Data Intelligence Platform, ensuring customer satisfaction and exceeding sales targets.

Databricks logo

Databricks

London, United Kingdom

£56,000 – £65,000 pa On-site Permanent Clearance Required

Bioinformatics Engineer (we have office locations in Cambridge, Leeds & London)

The Bioinformatics Engineer will develop and scale knowledge platforms that support the NHS Whole Genome Sequencing (WGS) Genomic Medicine Service. Key responsibilities include building APIs, data models, and pipelines for high-quality genomic data, collaborating with genomic data scientists and engineers, and ensuring clinical and biological accuracy in software. The role involves working in an agile team to deliver robust, testable, and clinically relevant systems.

Genomics England logo

Genomics England

Cambridge, Cambridgeshire, United Kingdom

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Career Advice

Advance your Data Engineering career with expert advice, practical job search tips, and insightful industry guides.

Products

Where to Advertise Data Engineering Jobs in the UK (2026 Guide)

Advertising data engineering jobs in the UK requires a different approach to most technical hiring. Data engineers occupy a distinct discipline that sits between software engineering, data science and cloud infrastructure — and the strongest candidates identify firmly with the data engineering community rather than with adjacent roles. General job boards consistently conflate data engineering with data analysis, data science and BI development, producing high application volumes but low candidate quality for specialist pipeline and platform roles. This guide, published by DataEngineeringJobs.co.uk, covers where to advertise data engineering roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.

Jobs

Data Engineering Jobs UK 2026: What to Expect Over the Next 3 Years

Data engineering has become one of the most strategically important disciplines in the entire technology sector — and one of the most reliably in-demand. Every organisation that wants to use data to make decisions, train AI models, personalise products, manage risk, or understand its customers depends on data engineers to build the infrastructure that makes any of that possible. Without well-designed, reliable data pipelines, the most sophisticated machine learning model is worthless and the most ambitious analytics strategy is undeliverable. That foundational importance has made data engineering hiring remarkably resilient through the technology market corrections of the past few years. Where headcount reductions fell heavily on some engineering disciplines, demand for data engineers held firm — because the work of building and maintaining data infrastructure cannot be deferred in the way that some product development can. The data keeps coming. The pipelines need to work. But the data engineering jobs market of 2026 is not simply a stable version of what it was three years ago. The discipline has undergone a series of architectural shifts — from batch to streaming, from on-premise data warehouses to cloud-native lakehouses, from hand-rolled pipelines to declarative transformation frameworks, and most recently toward AI-augmented data engineering workflows that are beginning to reshape what the role looks like in practice. The employers hiring data engineers today are asking for a meaningfully different skill set than those hiring three years ago. The candidates who will thrive over the next three years are those who understand where the discipline is heading — which architectural patterns are becoming standard, which technologies are defining the modern data stack, and how the definition of a data engineering career is evolving toward a richer intersection of infrastructure, analytics, and AI enablement. This article breaks down what the UK data engineering jobs market is likely to look like through to 2028 — covering the titles emerging right now, the technologies driving employer demand, the skills that will matter most, and how to position your career ahead of the curve.

Jobs

New Data Engineering Employers to Watch in 2026: UK and Global Companies Driving the Data Revolution

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.

Careers

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

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.

Jobs

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

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.

Education

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

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.

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