1 to 25 of 29 Remote Metadata Jobs in the Thames Valley

Databricks Certified, AWS/Azure/GCP Data Engineering certifications) Experience with DataOps, CI/CD practices, and infrastructure-as-code Knowledge of data governance, data quality frameworks, and metadata management Benefits: Hybrid/remote working environment, allowing you a flexible work-life balance to thrive both in the office and from the comfort of your home Competitive compensation package More ❯

vendor evaluation, implementation, and adoption across the enterprise. Establish and maintain reference data management frameworks and governance processes. Develop and execute data strategies, including future state architecture, data governance, metadata management, data privacy, reference data management, and data integration. Lead the design and review of data architectures for both operational platforms (APIs, event streams, transactional systems) and analytical platforms (data More ❯

e.g., Git, Azure DevOps). Desirable Exposure to Python or Scala for data engineering tasks. Knowledge of Power BI or other visualisation tools. Experience with data governance frameworks and metadata management. If you’re interested, get in touch ASAP with a copy of your most recent and up-to-date CV and email me at b.forbes@tenthrevolution.com or you can More ❯

that enable scalability and cross-business alignment. Design, build, and optimise data platforms leveraging cloud-native technologies (AWS, Azure, or GCP). Integrate key data management capabilities, including governance, metadata, privacy, and cataloguing. Act as a trusted advisor, translating complex technical concepts into clear business outcomes. Required Skills and Experience 10+ years of professional experience in data architecture, engineering, or More ❯

In-depth knowledge of database design, structures, and data mining techniques. Skilled in Kimball methodology and Data Vault modelling approaches. Strong understanding of database fundamentals and practical experience designing metadata-driven ingestion and transformation pipelines. Hands-on experience with Master Data Management (MDM), data cataloguing, and data lineage tracking. Advanced proficiency with Microsoft Azure data services, including Databricks, Azure Data More ❯

glossaries, and implement robust data quality frameworks Identify and manage internal and external data sources, ensuring strong access and sharing controls. AI & Technology Enablement Build tools and processes for metadata management, data quality, and data sharing. Leverage AI and automation tools to improve data governance capabilities. Use Python, SQL, PySpark, Power BI, and related tools for data processing and visualization. More ❯

non-technical stakeholders. Expertise in data modelling to at least 3NF, database structures, and data mining. Proficiency in Kimball methodology and Data Vaults . Strong understanding of database fundamentals, metadata-driven ingestion, and transformation pipelines. Experience with Master Data Management (MDM) , data cataloguing, and managing data lineage. Familiarity with Azure Cloud Services , including DataBricks, Azure Data Factory, Azure SQL, CosmosDB More ❯

user needs when designing deliverables. Experience in designing technology solutions with complex end-to-end data flows. Experience in implementing data governance, including data cataloging, data lineage tracking, and metadata management to ensure data accuracy, accessibility, and compliance. Preferred: Experience with Databricks Understanding of how data platforms interact with marketing and customer engagement platforms. Knowledge of service-oriented architecture, including More ❯

Streams & Tasks, and performance optimization Integration with AWS services and orchestration tools Expertise in data integration patterns, ETL/ELT, and data pipeline orchestration Experience with data quality frameworks, metadata management, and data lineage Hands-on experience with machine learning pipelines and generative AI engineering Familiarity with DevOps practices, CI/CD for data workflows, and infrastructure-as-code (e.g. More ❯

/LODs, and voxel/point-cloud conversions. Implement labeling and QA workflows, manage external annotation vendors, and automate quality checks to ensure scalable, reliable datasets. Define schemas and metadata for digital assets, maintaining catalogues, lineage, and versioning to ensure reproducibility and governance. Enforce data quality, drift detection, and compliance (GDPR/COPPA), including watermarking and traceability to safeguard IP More ❯

or performance bottlenecks—and apply robust fixes. Document resolutions to strengthen system resilience. 4. Design, Build, & Govern Data Products Architect, construct, and maintain reusable data products, embedding clean datasets, metadata, governance policies, and clearly defined data contracts. Ensure compliance with FAIR principles—data being Findable, Accessible, Interoperable, and Reusable—and enforce robust access controls in collaboration with governance stakeholders. 5. More ❯

or performance bottlenecks-and apply robust fixes. Document resolutions to strengthen system resilience. 4. Design, Build, & Govern Data Products Architect, construct, and maintain reusable data products, embedding clean datasets, metadata, governance policies, and clearly defined data contracts. Ensure compliance with FAIR principles-data being Findable, Accessible, Interoperable, and Reusable-and enforce robust access controls in collaboration with governance stakeholders. 5. More ❯

mismatches or performance bottlenecks—and apply robust fixes. Document resolutions to strengthen system resilience. Design, Build, & Govern Data Products Architect, construct, and maintain reusable data products, embedding clean datasets, metadata, governance policies, and clearly defined data contracts. Ensure compliance with FAIR principles—data being Findable, Accessible, Interoperable, and Reusable—and enforce robust access controls in collaboration with governance stakeholders. Translate More ❯

mismatches or performance bottlenecks—and apply robust fixes. Document resolutions to strengthen system resilience. Design, Build, & Govern Data Products Architect, construct, and maintain reusable data products, embedding clean datasets, metadata, governance policies, and clearly defined data contracts. Ensure compliance with FAIR principles—data being Findable, Accessible, Interoperable, and Reusable—and enforce robust access controls in collaboration with governance stakeholders. Translate More ❯

mismatches or performance bottlenecks-and apply robust fixes. Document resolutions to strengthen system resilience. Design, Build, & Govern Data Products Architect, construct, and maintain reusable data products, embedding clean datasets, metadata, governance policies, and clearly defined data contracts. Ensure compliance with FAIR principles-data being Findable, Accessible, Interoperable, and Reusable-and enforce robust access controls in collaboration with governance stakeholders. Translate More ❯

modular architecture. WebGL or Canvas-based rendering expertise for interactive medical or imaging UIs (LOD layers, measurement overlays, viewport coordination). Deep knowledge of DICOM/DICOMWeb workflows, imaging metadata, multi-series coordination, and medical data privacy considerations. Tooling fluency: Webpack 5, npm scripts, Dockerised deployments, Jest testing, ESLint/Prettier automation, and scalable state management patterns. Secure OAuth/ More ❯

related regulations and manage data-related risks. Support the Data Governance Manager in leading and facilitating council meetings, driving decision making processes, and ensuring alignment with organisational objectives. Implement metadata management processes to capture and maintain data lineage, definitions, and dependencies. Establish and maintain data dictionaries, glossaries, and cataloguing tools to support data discovery and documentation. Contribute to defining and … data stewardship, and data lifecycle management. Experience with MDM initiatives, ensuring data consistency and accuracy across the organisation. Familiarity with tools such as Azure Purview for data cataloguing and metadata management. Knowledge of records management and retention practices, with experience using tools such as SharePoint or other lifecycle management systems. Understanding of regulatory requirements and industry standards related to data More ❯

Key Responsibilities: - Data & Retrieval: Build ingestion pipelines for structured and unstructured data; design retrieval-augmented generation (RAG) systems; manage vector and keyword indexes; develop NLP and recommendation systems; implement metadata and tagging frameworks. - LLM & ML Applications: Develop and maintain ML and LLM models; build LLM apps with LangChain/LangGraph; apply multimodal AI, prompt engineering, fine-tuning, and model optimization More ❯

content deliverables are executed efficiently and support visibility improvements across the company and the Research & Policy Center (RPC) web properties. Key Responsibilities: Implement on-page SEO best practices including metadata, internal linking, keyword optimization and structural content updates Support technical SEO delivery and optimization across high-priority pages, ensuring crawlability, indexation, and site health Assist in implementing schema markup, structured More ❯

principles. Experience of working within, and influencing, international collaborations, including those within the Photon and Neutron community. Knowledge of the use of FAIR vocabularies and ontologies, Persistent Identifiers and metadata schemas (e.g. DataCite and domain-specific vocabularies). Ability to present complex concepts to both specialist and non-specialist audiences. Skills in managing multiple projects and systems and collaborating with More ❯

architecture and modernisation. Define enterprise data strategies, architecture principles, and implementation roadmaps. Design and deliver cloud-native data platforms (AWS, Azure, GCP) and integration frameworks. Embed governance, security, and metadata management into architecture design. Translate complex technical concepts into business outcomes for stakeholders. Oversee project delivery and mentor junior consultants. Required Experience 4+ years’ experience in data architecture, data engineering … cloud or data architecture (AWS, Azure, GCP, Databricks). Experience designing data lakes, data meshes, or large-scale migration programmes . Familiarity with graph data models , semantic modelling , or metadata tools . Background in consulting or experience leading transformation projects in regulated industries. Proven ability to lead teams and develop data architecture propositions. Why Join Shape enterprise data transformation for More ❯

triage and manage documentation lifecycle (e.g., maintain, archive, obsolete). Work closely with Document Controllers and service provider admins to implement disposition actions and track them to closure. Align metadata between internal and external DMS platforms to ensure lifecycle consistency. Drive improvements in external DMS functionality and design. Implement formal archiving processes for external documentation. Guide business users in accessing More ❯

triage and manage documentation lifecycle (e.g., maintain, archive, obsolete). Work closely with Document Controllers and service provider admins to implement disposition actions and track them to closure. Align metadata between internal and external DMS platforms to ensure lifecycle consistency. Drive improvements in external DMS functionality and design. Implement formal archiving processes for external documentation. Guide business users in accessing More ❯

triage and manage documentation lifecycle (e.g., maintain, archive, obsolete). Work closely with Document Controllers and service provider admins to implement disposition actions and track them to closure. Align metadata between internal and external DMS platforms to ensure lifecycle consistency. Drive improvements in external DMS functionality and design. Implement formal archiving processes for external documentation. Guide business users in accessing More ❯

triage and manage documentation lifecycle (e.g., maintain, archive, obsolete). Work closely with Document Controllers and service provider admins to implement disposition actions and track them to closure. Align metadata between internal and external DMS platforms to ensure lifecycle consistency. Drive improvements in external DMS functionality and design. Implement formal archiving processes for external documentation. Guide business users in accessing More ❯