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

Interest-free season ticket loans, electric vehicle and cycle to work schemes Up to 18 weeks of paid parental leave depending on your situation 28 days holiday plus bank holidays 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

Building data solutions

• 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.
• Monitor and troubleshoot data pipelines and services, identifying and resolving issues when they arise.

Technical delivery

• Contribute to technical decisions within projects, considering user needs, client requirements and the wider technical environment.
• Work within agreed technical and architectural approaches, while identifying where these may need to change or improve.
• Consider security, privacy, accessibility and responsible use of data as part of your work.
• Produce clear technical documentation so that others can understand, use and maintain the solutions you build.
• Learn and adapt to different technologies and platforms depending on the needs of the project.

Working with others

• Work collaboratively with developers, designers, researchers, delivery colleagues and other specialists as part of multidisciplinary teams.
• Communicate technical concepts clearly to colleagues and clients, including people without a data or engineering background.
• Take responsibility for your own work, raising risks or asking for support where appropriate.
• Participate in reviews, pairing and other collaborative engineering practices, sharing knowledge and learning from others.
• Contribute to the wider technology practice at dxw by sharing what you’ve learned and helping improve how we work.

About you

You:

• Want to work on digital services and technology that improve people’s lives.
• Have experience building and maintaining data pipelines and data infrastructure in a production environment.
• Have experience working with data modelling and transforming data into reliable, usable structures.
• Can write code for data processing and engineering, for example using Python, SQL or similar languages.
• Have experience with modern software engineering practices such as version control, automated testing and continuous integration/deployment.
• Have worked with cloud-based data technologies and are comfortable getting to grips with unfamiliar tools and platforms.
• Understand different approaches to storing and processing data, such as data warehouses, lakes and lakehouses, and can choose appropriate approaches for the problem you’re working on.
• Understand the importance of data quality, security, privacy and good data governance.
• Can investigate technical problems, weigh up different options and make sensible decisions within the context of a project.
• Communicate clearly and work well with people from different disciplines and levels of technical knowledge.
• Enjoy variety in your work and are comfortable working through problems where the answer isn’t always clear at the outset.

We’re flexible about the particular technologies you’ve worked with. Depending on the project, our data work might involve tools and platforms such as Python, SQL, Snowflake, Databricks, Redshift, Airflow, Dagster, Terraform, Azure Data Factory or AWS Glue. Experience with every one of these isn’t expected but adaptability and willingness to try new tooling is.

About dxw

dxw works with organisations in the public, non-profit and private sectors to build usable and accessible digital services that fit seamlessly into users’ lives.

We’re an employee-owned agency of technology, design and delivery experts. We help organisations make better use of technology and data, creating services that work well for the people who need them.

Recent projects include improving access to adult social care, supporting the rehabilitation of people leaving prison, and many more.

One of the things that makes us different is that we are employee-owned, so we are not beholden to external shareholders and are protected against being taken over by private equity. It also means we can prioritise being an inclusive employer, reducing our impact on the planet, and working in the open. We particularly encourage applications from people who are underrepresented in tech and/or looking for flexible working arrangements.