Data Engineer

Salary £60,000-£65,000 (FTE, per annum) Contract Full-time, permanent, with flexible working options available. Location Anywhere in the UK, with some national travel required to meet teams and clients. Office locations are London and Leeds. Co-working spaces are available across the UK. Application deadline 29/10/2026

Benefits include

• Interest-free season ticket loans, electric vehicle and cycle to work schemes
• Up to 18 weeks of paid parental leave depending on your situation
• Pension with up to 6% matching contribution from dxw
• Flexible working to support your wellbeing and personal commitments
• Macbook and home office setup budget

About the role

As a Data Engineer at dxw, you’ll work as part of multidisciplinary teams to design, build and maintain data solutions for our clients.

You’ll help turn data from different sources into reliable, usable and well-structured datasets, building the pipelines and infrastructure needed to collect, transform, store and make data available. You’ll work closely with other technologists and colleagues across disciplines to understand what’s needed and choose appropriate approaches.

The exact technologies and challenges will vary from project to project. More often than not, our clients have their own established tooling, platforms and processes, which we need to work within rather than change. On other projects we’re involved from the start and help decide which tools and technologies to use. Either way, you’ll need to be comfortable picking up new tools quickly, working effectively in different client environments, and knowing when to adapt to what’s already there and when to recommend a different approach.

Key responsibilities

• Design, build and maintain data pipelines that collect, transform and move data between systems.
• Develop reliable and maintainable data models that make data useful and accessible.
• Work with a wide range of data types and sources, including structured data such as relational databases and spreadsheets, semi-structured data such as JSON, XML and logs, and unstructured data such as documents, free text and images. Handle data at different scales, from small, one-off datasets to large volumes that need efficient processing, while understanding each source’s structure, quality and limitations.
• Support AI readiness and data solutions in projects, which may include AI for data in deployed services, preparing data for machine learning, and other AI applications.
• Apply AI coding and other data handling tools responsibly in engineering work.
• Build and maintain data infrastructure using appropriate cloud services and data platforms.
• Apply modern software engineering practices to data work, including version control, automated testing, deployment and observability.