Microsoft Fabric Data Platform Architect (London, ENG)
Posted Updated
Summary
Leads enterprise data strategy and the modernisation of a large organisation's data estate onto a unified Microsoft Fabric platform on Azure. Day to day: architecture and governance of lakehouse/warehouse patterns, scalable ingestion, integration APIs, data lineage/MDM, and managing data solutioning teams.
Microsoft Fabric Data Platform Architect is required by a large organisation to lead the enterprise data strategy and the integration of the company's systems into a unified data ecosystem.
You will be responsible for:
- Leading the modernisation of the current data estate.
- Leading the architecture, design, and governance of the enterprise Microsoft Fabric platform.
- Designing scalable data ingestion and data storage solutions.
- Defining standards and architectural patterns across Lakehouse, Data Warehouse, and Data Engineering domains.
- Providing technical leadership and architectural assurance through design reviews and governance processes.
- Designing enterprise integration architectures, APIs, and event-driven patterns across the data landscape.
- Embedding metadata-driven architecture principles to improve automation, governance, and operational efficiency.
- Maintaining the enterprise data architecture roadmap.
- Establishing master data management principles and supporting teams in defining authoritative data sources.
- Implementing data lineage, data ownership, metadata management, access controls, and security policies across the data platform.
- Managing data solutioning teams.
Required Experience
- Extensive experience in enterprise data architecture, solution architecture, or data platform leadership, with deep hands-on expertise in Microsoft Fabric.
- Proven track record of integrating various ERP and CRM platforms, ideally including Salesforce and Microsoft Dynamics.
- Strong experience designing enterprise-scale cloud data platforms and modern data architectures across the Azure Data Platform ecosystem.
- Advanced experience in data modelling, lakehouse/warehouse design patterns, SQL optimisation, and API-based ingestion architectures.
- Proven experience implementing metadata-driven architecture, data lineage, cataloguing, and master data management (MDM).
- Strong understanding of data governance frameworks, data quality, and enterprise data integration patterns.