We work with some of the UK's biggest companies and government departments to provide a pragmatic approach to technology, delivering bespoke software solutions and expert advice.
Drive data discovery work, work with stakeholders providing or consuming data, and provide clarity and insight for our teams.
Dig into raw, unfamiliar data, frequently at scale and in production, to work out what is there, how it fits together, and where it can and can't be trusted.
Separate genuine data issues from quirks of history, size the impact and risk, and give data engineers the clear, evidenced picture they need to build reliable data models.
Guide clients in extracting the most value and impact from their data.
Diagnose anomalies and work out solutions.
Requirements
Significant experience profiling and investigating large, complex datasets at scale and in production.
Experience with technologies such as SQL, Spark and Python, and you're confident querying analytical data directly rather than relying on pre-built reporting.
You're a problem-solver who works independently, with the judgement to direct your own investigations.
You can gather and shape requirements through conversations and workshops, inform priorities, and work within the governance and access controls around sensitive data.
Hands-on data presentation, analytics and dashboarding skills – both to help understand how data is consumed, and for ad hoc presentational work.
Strong communication skills and a collaborative approach, comfortable presenting findings to senior client stakeholders, influencing decisions and constructively challenging when the evidence points the other way.
Tech Stack
Python
Spark
SQL
Benefits
25 days' annual leave, rising incrementally to 30 days after six years of service.
Generous family leave policies.
Access to an employer pension scheme and Group Life Assurance.
A range of optional benefits such as discounted gym membership and a cycle-to-work scheme.
A meaningful approach to evaluating your performance and providing feedback on your progress.