Data Engineer

Provide
Milton Keynes, United Kingdom
3 weeks ago
£65,000 pa

Salary

£65,000 pa

Job Type
Permanent
Work Pattern
Full-time
Work Location
On-site
Seniority
Mid
Education
Degree
Posted
6 May 2026 (3 weeks ago)

As a Data Engineer, you will collaborate with a wider data and technology function to build scalable, reliable data solutions. You’ll contribute to the evolution of a shared data model, support ingestion from multiple sources, and ensure high standards across data quality, performance, and governance.

You’ll be involved in both project delivery and ongoing platform improvement, working in an agile environment alongside engineers, analysts, and stakeholders.

Key Responsibilities
  • Design and implement robust data pipelines to ingest, transform, and deliver data from a variety of internal and external sources
  • Contribute to the development and maintenance of a centralised data model used across the organisation
  • Apply best practices in data architecture, modelling, and pipeline design to ensure scalability and consistency
  • Investigate and resolve data-related issues, ensuring timely fixes within agreed service levels
  • Work closely with cross-functional teams to deliver data solutions aligned with business objectives
  • Monitor and optimise data workflows to improve performance, reliability, and accessibility
  • Support continuous improvement of data engineering standards, tooling, and processes
Skills & Experience
  • Proven experience in a Data Engineering or similar role
  • Strong hands-on capability withPython and SQL for data processing and transformation
  • Experience working withdistributed data processing frameworks (e.g. Spark)
  • Solid understanding ofdata modelling and data warehousing concepts
  • Experience building and maintainingETL/ELT pipelines in production environments
  • Exposure tocloud platforms such as Azure, AWS, or GCP
  • Familiarity withmodern data architectures (e.g. lakehouse or layered approaches such as Bronze/Silver/Gold)
  • Strong problem-solving skills, with experience handling incidents and maintaining data reliability
  • Comfortable working in agile delivery environments and collaborating with technical and non-technical stakeholders
Desirable
  • Experience with Azure-based tooling (e.g. data integration services, analytics platforms)
  • Familiarity with version control, CI/CD, and deployment processes for data pipelines
  • Experience with collaboration tools such as Jira and Confluence
  • Relevant certifications in data engineering or cloud technologies
  • STEM degree or equivalent practical experience

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Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

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

Where to advertise data engineering jobs UK in 2026: the specialist boards and channels that reach Spark, dbt, Snowflake and platform engineering talent. 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.

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

Data Engineering Jobs UK 2026: roles, salaries and the trends shaping UK data engineering hiring over the next three years — Spark, dbt, lakehouse and AI. 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.