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Data Solutions Architect

Tesco
5 days ago
Full-time
Remote friendly (City of Edinburgh, Scotland, United Kingdom)
Worldwide
£80,000 - £90,000 GBP yearly
Solutions Architect
Tesco Insurance Edinburgh - 2 South Gyle Crescent, Edinburgh, EH12 9FQ Permanent Apply by 22-Oct-2026
About the role

Serving our customers, communities, and planet a little better every day.

Salary - Between £80,000 - £90,000 (DOE) + annual bonus & benefits
Work Level - 2
Location – Edinburgh, Permanent
Office Attendance – Our hybrid working model gives you the best of both worlds - flexibility to work from home and valuable face-to-face time with colleagues. This role typically requires 2 days per week onsite.
Closing Date - Applications close on 22nd October at 5pm

Why this role?
We’re looking for a Data Solutions Architect to play a key role in shaping and delivering data services utilising our new Microsoft Fabric data platform within Tesco Insurance and Money Services.  
 
This is a pivotal role at a critical point in our data journey. You’ll provide key technical and architectural skills across data modelling, analytics and platform design, ensuring our data foundations are robust, governed and built for long term use. You’ll work closely with engineers, analysts, product teams and senior stakeholders to translate business and regulatory needs into clear, scalable data architectures.  
 
The role combines strategic design with a particular focus on high quality conceptual, logical and physical data models that underpin analytics, reporting, AI and operational use cases across the organisation.

What you’ll be doing 
• Define and own data architecture patterns, standards and target state designs for our Microsoft Fabric platform, ensuring consistency across ingestion, storage, semantic modelling and consumption layers.  
• Develop next-generation platform capabilities, including real-time ingestion, AI-driven insights and API-led integration 
• Lead the design and governance of enterprise and domain data models, from conceptual and logical models through to physical implementations optimised for Fabric (Lakehouse, Warehouse and semantic models).  
• Partner with data engineers, analytics engineers and platform teams to ensure data models are correctly implemented, performant and aligned to architectural intent.  
• Shape and assure the semantic layer (e.g. shared dimensions, f