Senior Data Modeller / Analyst (Graph)
£70,000 - £80,000 per annum
Fully Remote, occasional trips into Reading or London (1-2 times per year)
Telecoms
Do you enjoy working out how messy, undocumented data actually fits together, and then designing something better?
I’m working with a specialist engineering consultancy that modernises and migrates critical platforms for big telecoms and financial services organisations. They’re hiring a Senior Data Modeller to join a large transformation programme for a major UK mobile and broadband operator.
The programme has about seven workstreams, and each needs serious data analysis and modelling. You’ll sit alongside the engineering team and take real modelling work off their plate from day one. This role is about modelling and analysis. It isn’t data engineering, and there’s no dashboarding, reporting or development work.
What you’ll be doing
🔍 Analysing source systems to understand their structure, relationships and data quality, often without a subject matter expert to lean on
🧩 Reverse engineering and documenting data models where the documentation is thin or missing
🕸️ Designing graph data models that represent complex relationships and support efficient traversal
📐 Building conceptual, logical and physical target models that bring together data from several source systems
What they’re looking for
✅ Hands-on graph database modelling experience. Neo4j is ideal, and Neptune or Gremlin are also relevant
✅ Strong SQL for querying, profiling and validating large datasets
✅ Proven experience modelling complex enterprise data that comes from several sources
✅ A solid grasp of how model design affects query performance and scalability
✅ Experience on a cloud platform (GCP, AWS or Azure)
The details
📍 Fully remote (UK), with the odd optional office visit
💰 £70,000 - £80,000 per annum
⚡ Quick process: technical interview with two of the engineers, then a short final chat with engineering leadership
If this sounds like you, or you know someone it would suit, send me a message or apply directly.