Work with Us

The work

You’ll deliver real, production data engineering across our client projects:

• Designing, building, and optimising ETL processes and data pipelines
• Contributing robust data models and schemas that support analytics and reporting
• Building data warehouse and lakehouse solutions on the Microsoft data platform, including work with columnar formats such as Parquet
• Working with Azure DevOps and CI/CD pipelines to deploy and maintain data solutions
• Implementing data quality checks and documenting your deliverables
• Working with both structured and unstructured data

Engagements are project-based and fully remote, arranged as client demand arises. You’ll work independently on defined deliverables, liaising with the Dataqubed team as needed to align with client requirements.

What we’re looking for

• Demonstrable, hands-on data engineering ability - you can build and deliver a data pipeline from a specification, independently and to a high standard. This may come from professional roles, project work, or substantial research/academic work.
• Sound data modelling skills and the ability to design schemas that support analytics and reporting.
• A core command of ETL processes and the tools and frameworks used to implement them.
• Understanding of data warehousing and data lake principles, including columnar formats such as Parquet and lakehouse architectures. We work on the Microsoft data platform, with a preference for Microsoft Fabric.
• Core proficiency in SQL and Python.
• Experience with Azure DevOps, including authoring pipelines via YAML configuration.
• Active Microsoft certifications (e.g. Azure, Fabric, or other data-related credentials) are a bonus, but not essential. Comfort with data analytics and BI, including producing outputs in tools such as Power BI.
• An appreciation of compliance and data integrity in regulated sectors is a plus.

We especially like working with people who bring a scientific or research mindset to their engineering - it’s how we think, and how we build. That said, the work suits people from non-science and research backgrounds too.

How to apply

Send us a short summary of the data engineering work you’ve delivered - professional, freelance, or project-based - along with your CV and availability, to work@dataqubed.com. If you’re a fit, we’ll be in touch.

What you’ll do:

• Administration and paperwork: invoicing and payment follow-up, contractual documents through to signature, record-keeping to assist our compliance team (we operate an ISO-certified management system)
• Calendar and meeting support - setting up appointments, confirming meetings, making sure follow-ups happen and nothing slips
• Support onboarding and offboarding of team members and clients - accounts, access, paperwork, and welcome/wrap-up steps done properly Help organise our digital assets - files, documents, and shared workspaces - so everything remains easy to find and consistently structured
• Research tasks and travel booking

Who you are:

• Meticulous and dependable; you notice loose ends and close them
• Proactive and responsive
• Naturally organised - if you find yourself doing something twice, your instinct is to build a system for it
• If you know something can be improved, you’re not afraid to propose it
• Comfortable using AI tools to work smarter, but you know when a task needs human judgement
• Confident with Microsoft 365, and open to learning new tools, skills, and ways of working
• Clear, professional writing and complete discretion with sensitive information

Details:

• Part-time, 10 hours a week - flexible, with scope to increase hours as the company continues to grow
• Fully remote
• Competitive rate/salary, dependent on experience

To apply, email work@dataqubed.com with a short note on your relevant experience with your latest CV. Applicants must have the right to work in the UK. Dataqubed is an equal opportunity employer and welcomes applications from all suitably qualified candidates.