126 to 150 of 625 Metadata Jobs in the UK

enrichment, focusing on the most critical data first and tracking the tangible ‘value-add’ with data consumers. \n Ensure Compliance & Transparency: Maintain complete metadata, data descriptions, and lineage while ensuring data is correctly classified, protected, and compliant with GDPR and internal security protocols. \n Manage Risk & Alignment: Engage with stakeholders ...

GenAI within a governed environment Ensure the platform supports secure access to structured and unstructured data, including client, matter, financial and document metadata Define and enforce data governance, quality and compliance, working closely with Risk, Privacy and Information Security teams Act as the primary business and leadership for the data ...

time to value. Co-build and hand off. Work alongside customer technical teams and partners through pairing, code reviews, and configuration reviews. Package reusable metadata, scripts, queries, tests, and runbooks so the solution can be reproduced and supported. Support deployment, validation, production handoff, and early stabilization, leaving clear ownership ...

agents and business decision‐making. Consolidate, cleanse and structure information from Salesforce, event platforms, marketing systems and operational tools. Define practical data‐quality, metadata and governance standards for information used by Agent Factory. Identify trends, risks and commercial or operational opportunities within WWE datasets. Support secure, reliable data flows between ...

time to value. Co-build and hand off. Work alongside customer technical teams and partners through pairing, code reviews, and configuration reviews. Package reusable metadata, scripts, queries, tests, and runbooks so the solution can be reproduced and supported. Support deployment, validation, production handoff, and early stabilization, leaving clear ownership ...

pricing, reference data, benchmarks, , performance, risk, sustainability). Familiarity with data platform concepts such as batch/stream processing, orchestration patterns, data lineage/metadata, and data quality monitoring. Experience working in Agile or hybrid delivery models (backlog refinement, sprint ceremonies, defining “definition of ready/done”). Exposure ...

technical debt across the data ecosystem. Own the Data as a Product Community of Practice and the standards that bind every Data Product: metadata and data contract specifications, output port and schema design, data product versioning, DQ requirements, SLA and SLO declarations, and semantic layer conventions Champion data quality, lineage ...

products that are discoverable, versioned, self-describing, and aligned with data mesh and product-centric principles Establish best practices for product design, schema management, metadata standards, lineage, and lifecycle governance Ensure data products are optimized for performance, scalability, reliability, and cost efficiency Promote consistency across product domains while enabling autonomy … Technical Leadership & Standards Serve as a senior technical authority for data product architecture across the program Define architectural best practices for Delta Lake design, metadata management, product lifecycle governance, and data quality controls Provide architecture assurance and design reviews for data products developed by internal and third-party teams Guide ...

delivery teams. Provide technical leadership on data management, data integration, analytics, reporting, and Business Intelligence solutions. Support the implementation of robust data governance, metadata management, and data quality frameworks. Collaborate with architects, developers, analysts, and stakeholders to deliver modern data solutions. Produce architecture documentation and present recommendations to senior stakeholders. … Knowledge of modern analytics and BI technologies such as Power BI, Tableau, or similar tools. Strong understanding of data governance, data quality, lineage, and metadata management. Experience defining architecture standards, patterns, and best practices. Ability to engage with senior stakeholders and translate business requirements into technical solutions. Strong documentation ...

analytics objectives. Key Responsibilities Define and maintain enterprise data architecture standards and roadmap Develop target-state data architecture and transformation strategy Drive data governance, metadata, data quality, and master data capabilities Provide architectural leadership across analytics and reporting initiatives Work closely with business stakeholders to align data strategy with organisational ...

hands‐on experience with IBM Cognos Analytics . Strong experience in Cognos Development and Administration . Cognos report development and troubleshooting. Framework Manager/metadata modelling knowledge. Cognos security, users, groups, roles, and permissions. Report scheduling, jobs, deployments, and environment management. Performance monitoring and troubleshooting. Strong SQL and relational database ...

logical and physical). Experience with modern data platforms, data warehouses and cloud-based data solutions. Strong understanding of data governance, data quality and metadata management. Excellent stakeholder engagement and communication skills. Essential Requirements To be considered for this role, you must hold: Live SC (Security Check) clearance Live NPPV ...

with AI Engineering Leads, Data Engineers and client architects to ensure solutions align with enterprise standards and constraints. Define data governance, data quality and metadata practices required to support trusted analytics and AI. Provide architectural oversight across programmes, reviewing designs and guiding trade‐off decisions. Evaluate and recommend data ...

models. Shaping modern data platforms, integrations and enterprise data flows. Supporting trusted reporting, analytics, automation and appropriate AI use cases. Embedding data quality, security, metadata, lineage and lifecycle requirements. Providing architecture leadership and assurance across complex change initiatives. Mentoring technical colleagues and improving data architecture capability. What we are looking ...

preferred) Track record managing complex, multi-stakeholder engagements Must-Have Knowledge GDPR, DPDP Act, CCPA/CPRA, HIPAA — practical application Data classification frameworks and metadata management Cloud-native data architectures and hybrid environments Certifications (Preferred) BigID Certified Professional CIPP/E, CIPM (IAPP) Soft Skills Exceptional client communication — written, verbal ...

handling effective and compliant, meeting regulatory requirements for storage, retention, deletion and classification Contribute to the Electronic Document Management System, ensuring effective structure and metadata, compliant access controls, reporting and operational oversight Support effective data governance across the business, including policies, standards and procedures Establish and enforce data quality standards ...

designing scalable batch/stream processing patterns. Deep lakehouse and data platform expertise(e.g., Delta Lake concepts, schema evolution, data quality frameworks, lineage/metadata, and governance patterns) applied in production environments. Strong DevSecOps and platform engineering capability, including CI/CD design, automated security/quality gates, observability (logs ...

platform codebase where appetite and skill allow Keep QA coverage current as new views and data sources are onboarded — updating baselines, refreshing metadata, and extending test coverage without being asked Engage with AI agents for test authoring, investigation, result analysis, and documentation — working fluently in an AI-augmented engineering environment ...

ownership and stewardship models, target operating models, data architectures and implementation roadmaps. Strong understanding of master data management, data quality, data migration, data integration, metadata, reporting and analytics, with the ability to connect these disciplines into a coherent client solution. Experience leading large, distributed and multidisciplinary delivery teams, including onshore ...

adopting strategic tooling and assets. What you’ll bring Essential criteria: Demonstrated expertise across data management and data governance, including data ownership, data quality, metadata management, data lineage and data cataloguing. Proficiency with data management and data governance technologies and tooling. Experience supporting the design and implementation of Data & Information ...

through discovery, design, build, validation and release, while maintaining clear separation between product outcomes and delivery execution. Data Governance, Quality & Controls: Define ownership, lineage, metadata, access controls, reconciliation and quality expectations so that premium data is trusted, auditable and suitable for authorised use. Adoption & Value Realisation: Define success measures, monitor ...

through discovery, design, build, validation and release, while maintaining clear separation between product outcomes and delivery execution. Data Governance, Quality & Controls: Define ownership, lineage, metadata, access controls, reconciliation and quality expectations so that premium data is trusted, auditable and suitable for authorised use. Adoption & Value Realisation: Define success measures, monitor ...

through discovery, design, build, validation and release, while maintaining clear separation between product outcomes and delivery execution. · Data Governance, Quality & Controls: Define ownership, lineage, metadata, access controls, reconciliation and quality expectations so that premium data is trusted, auditable and suitable for authorised use. · Adoption & Value Realisation: Define success measures, monitor ...

Board level Data Deep expertise in data management disciplines, including: Data governance and stewardship models Data management and controls Master and reference data management Metadata management and data lineage Experience establishing and scaling a data governance function (policies, frameworks, controls, ownership models) Strong understanding of data architecture principles, including modern ...

capabilities supporting multiple of technology assets. Establish engineering standards, design patterns, and platform guardrails for telemetry collection and observability data management. Drive adoption of metadata‐driven routing, schema normalization, data classification, and governance across enterprise logging ecosystems. Build highly resilient, scalable, and cost‐efficient telemetry pipelines capable of handling large ...