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Microsoft Fabric Data Platform Architect
London, England, United Kingdom
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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.
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