Solution Architect for Data Modelling in Analytics

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The Solution Architect for Data Modelling is responsible for defining and governing enterprise-level data models across an analytics platform ensuring consistency scalability and alignment with business and technical requirements. This role involves designing logical data models establishing standards and best practices collaborating with stakeholders and data engineers and overseeing implementation in tools like Databricks. The architect also supports data governance validates deliverables drives continuous improvement in modelling practices and tooling and acts as a subject matter expert guiding data architecture and platform evolution.

How you will make an impact

• Act as Solution Architect for Data Modelling defining and governing logical and conceptual data models across the Analytics Platform (EDP)
• Design and maintain enterprise-level logical data models ensuring consistency reuse and scalability across domains
• Lead data modelling activities in Databricks (Delta Lake) and support integration with modelling tools such as Erwin DM/DI
• Define and enforce data modelling standards naming conventions and best practices across the platform
• Collaborate closely with Data Engineers to ensure correct implementation of models in Databricks
• Align modelling approach with enterprise data architecture governance frameworks and data domain ownership (Data Mesh / Data Products where applicable)
• Review and validate data models delivered by external vendors and delivery teams to ensure quality and compliance
• Drive continuous improvement of modelling practices tooling (Databricks Fabric) and automation capabilities

Your Background

• 5 years of experience in data architecture / data modelling / analytics solutions with strong focus on logical data modelling
• Proven experience designing enterprise data models (conceptual logical and physical) in complex data environments
• Hands-on experience with Databricks (Delta Lake) and understanding of lakehouse architecture principles
• Experience with data modelling tools (e.g. Erwin DM/DI or similar) including metadata and lineage management Experience working with Azure data services (e.g. ADLS ADF Fabric) is an advantage
• Strong knowledge of data modelling techniques (3NF dimensional modelling Data Vault concepts)
• Ability to translate business requirements into scalable and reusable data structures experience in global / distributed environments with strong communication skills in English

More about us

We pride ourselves on offering a holistic range of competitive benefits to support your financial physical and mental wellbeing and personal development. We want you to truly thrive with us in work and out.

We can provide more information during the recruitment process.

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