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# Data Architect

- **Company:** Open GI
- **Location:** Worcestershire, UK
- **Salary:** £57,753.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Microsoft Azure, Big Data, Cloud Engineering, Customer Data Management, Data Architecture, Data Governance, Data Migration, Data Visualization, Cloud Services, Data Streaming, Technical Debt, Data Lakes, Data Management, Physical Data Models, Databricks
- **Published:** August 15, 2026
- **Apply:** https://www.adzuna.co.uk/jobs/details/5842128686

## About the Role

* Strong knowledge of enterprise data architecture patterns and integration approaches (batch, streaming, event-driven, medallion, big data).
 * Demonstrable experience in running long-term data migration projects between bespoke systems desirable.
 * Experience with cloud data platforms - Azure (desirable) & Databricks (essential).
 * Advanced data modelling expertise, using industry reference models where appropriate.
 * Proven stakeholder engagement and communication skills.
 * Experience operating in the insurance industry is desirable but not essential.

## Description

The Data Architect defines and evolves the organisation's enterprise-wide data architecture to enable the evolving product strategy, analytics, and company-wide transformation. The role ensures data is consistent, secure, scalable, and fit for purpose across the enterprise.

Your key responsibilities

 * Define enterprise data architecture principles, standards, and roadmaps.
 * Design and maintain conceptual, logical, and physical data models.
 * Guide use of data platforms (data lakes, data visualisation, integration buses).
 * Enable high-quality data for client-facing products (reporting, AI/ML) and operations.
 * Co-author data governance practices with the Data Governance Lead: metadata, data quality, lineage, privacy, compliance within Databricks Unity Catalog.
 * Review solution designs for architectural alignment and risk reduction, eliminating duplication and maximising reusability at cost-efficient scale.
 * Evaluate emerging technologies and reduce technical debt.
 * Mentor and provide direction to data and engineering teams.
 * Establish effective guardrails to ensure smooth migration of customer data between heritage and modern cloud platforms at scale.


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