4 of 4 Metadata Jobs in Warwickshire

data mesh concepts such as data as a product, domain ownership, and federated governance. Demonstrated experience in data governance, including stewardship, policy implementation, and metadata management. Knowledge of JIRA and agile delivery practices. Effective communicator with the ability to translate complex data issues for diverse audiences. We value diversity ...

current-state assessment, target-state OT data architecture, logical data models, source-to-target mapping principles, data product standards, metadata and lineage requirements, normalisationpatterns,and governance recommendations. Proven experience in enterprise or solution data architecture within complex environments. Strong capability in conceptual,logicalandcanonicaldata modelling. Experience designing data products,standardsand governance ...

aware, and traceable answers. This position encompasses ownership of the architecture, standards, governance, design assurance, and roadmap for various knowledge management components, including taxonomy, metadata, and retrieval systems. Key Responsibilities: Architecture & Governance: - Own and define the enterprise knowledge architecture, principles, and roadmap aligned with AI and data strategies. - Establish … govern standards for taxonomy, metadata, content structure, and knowledge lifecycle management. Search & Retrieval: - Set architecture requirements for enterprise search and retrieval, ensuring AI responses are sourced from approved and traceable knowledge. - Use evidence-based insights to identify and prioritise improvements in architecture and content quality. Quality & Lifecycle Management: - Define controls ...

aware, and traceable answers. This position encompasses ownership of the architecture, standards, governance, design assurance, and roadmap for various knowledge management components, including taxonomy, metadata, and retrieval systems. Key Responsibilities: Architecture & Governance: - Own and define the enterprise knowledge architecture, principles, and roadmap aligned with AI and data strategies. - Establish … govern standards for taxonomy, metadata, content structure, and knowledge lifecycle management. Search & Retrieval: - Set architecture requirements for enterprise search and retrieval, ensuring AI responses are sourced from approved and traceable knowledge. - Use evidence-based insights to identify and prioritise improvements in architecture and content quality. Quality & Lifecycle Management: - Define controls ...