The work
You’ll deliver real, production data engineering across our client projects:
- Building and optimising ETL processes and data pipelines
- Contributing 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, to a high standard. This may come from professional roles, project work, or substantial research or academic work.
- Sound data modelling skills and the ability to design schemas that support analytics and reporting.
- A working command of ETL processes and the tools and frameworks used to implement them.
- Understanding of data warehousing and data lake principles, including 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 in YAML.
- Hands-on experience prompting AI tools, and a clear view of why a human stays in the loop.
- Active Microsoft certifications (Azure, Fabric or other data credentials), comfort with BI outputs in tools such as Power BI, and an appreciation of compliance and data integrity in regulated sectors are all bonuses, but not essential.
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. The work suits people from non-science backgrounds too.
You’ll need to be reachable during UK working hours (GMT/BST, +/- 2 hours). We need someone we can get hold of when it matters.
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.