101 to 125 of 628 Metadata Jobs in the UK

data architecture transformation Experience with business capability models, process taxonomies and maturity assessments Experience designing or governing data platform architectures , including data quality, metadata, security, privacy and compliance Understanding of public and private cloud architectures Experience with hyperscale and enterprise platforms (e.g. SAP, Workday, Oracle, Salesforce, public cloud providers) Experience ...

Have Experience with TypeScript or JavaScript Experience contributing to frontend applications (React) Familiarity with observability tooling (logging, monitoring, tracing) Experience with data modelling and metadata management Exposure to CI/CD practices for data pipelines and services Experience working in delivery-focused, agile environments Please note: We offer flexible hybrid ...

Python. Use data & artificial intelligence tools (e.g., AWS, CoPilot, Snowflake, DataBricks, LLM). Understanddata management and governance, including data platforms, pipelines, models, taxonomies, metadata, lineage, privacy, and regulatory compliance. Applystrong quantitative and analytical problem-solving skills to design experiments and deliver measurable outcomes (e.g., key performance indicators, uplift, return ...

experience to drive transparency and optimisation. Change leadership and enablement, including training, communications and community-building for data producers and consumers. Information architecture and metadata management for both structured and unstructured information. Demonstrated use of AI and digital tools to improve speed, quality and compliance in day-to-day work. ...

READ codes. Experience with Databricks. Experience with Kubernetes. Experience using Dagster or other workflow orchestration platforms. SQL and data modelling experience. Understanding of metadata management and data governance frameworks. Many Data Engineering roles focus primarily on building pipelines. This role is different. The greatest challenge is ensuring that every pipeline ...

supply chain, or franchise business models preferred.**Skills Requirement:****Data Management & Governance*** Enterprise Master Data Management (MDM)* Data Governance* Data Stewardship* Data Quality Management* Metadata Management* Reference Data Management* Business Glossary Management* Data Lifecycle Management* Data Standards & Policy Management* Data Operating Model Design**Technology & Platforms*** MDM Platform Strategy and Implementation ...

Data Science. End-to-End Capabilities: You understand the full lifecycle of data: discovery, storage, pipelines, ETL, and streaming, right through to data quality, metadata management, and advanced analytics for core decision-making. Data Product Mentality: You design Data Products ensuring that every pipeline and dataset is discoverable, addressable ...

Define Data Ownership, Data Stewardship, RACI and decision rights. Establish governance forums, councils and escalation mechanisms. Define and implement governance processes covering: Data Quality Metadata Management Business Glossary Data Classification Data Ownership & Stewardship Data Controls Master & Reference Data Define governance KPIs and maturity measures. Drive adoption of governance practices across ...

Define Data Ownership, Data Stewardship, RACI and decision rights. Establish governance forums, councils and escalation mechanisms. Define and implement governance processes covering: Data Quality Metadata Management Business Glossary Data Classification Data Ownership & Stewardship Data Controls Master & Reference Data Define governance KPIs and maturity measures. Drive adoption of governance practices across ...

captured once and can be used confidently across the business. Build a lightweight and effective data governance and quality framework covering accuracy, completeness, consistency, metadata, classification, privacy and security. Analytics & Business Intelligence Raise the quality and effectiveness of reporting and analytics across Humantra, ensuring leaders and teams have access ...

quality and enrichment, focusing on the most critical data first and tracking the tangible ‘value‐add’ with data consumers. 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. Manage Risk & Alignment: Engage with stakeholders ...

quality and enrichment, focusing on the most critical data first and tracking the tangible ‘value-add’ with data consumers. 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. Manage Risk & Alignment: Engage with stakeholders ...

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 ...

minimal redundancy. Partner with application development, architecture and business teams to define data strategies, data flows and source-to-target mappings. Develop and maintain metadata, data dictionaries and documentation to support enterprise data governance. Optimise and enhance existing data models to support new business initiatives and improve performance. Define … Experience working with relational databases and modern NoSQL platforms. Knowledge of ETL processes, data integration and data transformation techniques. Experience defining enterprise data standards, metadata management and naming conventions. Experience documenting data architecture, business rules, data dictionaries and technical specifications. Familiarity with UML and business process modelling techniques. Experience facilitating ...

minimal redundancy. Partner with application development, architecture and business teams to define data strategies, data flows and source-to-target mappings. Develop and maintain metadata, data dictionaries and documentation to support enterprise data governance. Optimise and enhance existing data models to support new business initiatives and improve performance. Define … Experience working with relational databases and modern NoSQL platforms. Knowledge of ETL processes, data integration and data transformation techniques. Experience defining enterprise data standards, metadata management and naming conventions. Experience documenting data architecture, business rules, data dictionaries and technical specifications. Familiarity with UML and business process modelling techniques. Experience facilitating ...

minimal redundancy. Partner with application development, architecture and business teams to define data strategies, data flows and source-to-target mappings. Develop and maintain metadata, data dictionaries and documentation to support enterprise data governance. Optimise and enhance existing data models to support new business initiatives and improve performance. Define … Experience working with relational databases and modern NoSQL platforms. Knowledge of ETL processes, data integration and data transformation techniques. Experience defining enterprise data standards, metadata management and naming conventions. Experience documenting data architecture, business rules, data dictionaries and technical specifications. Familiarity with UML and business process modelling techniques. Experience facilitating ...

data storage solutions across cloud and on-prem environments Apply DataOps/software engineering best practices for deployment and reliability Ensure strong data governance, metadata management and security controls What theyre looking for Strong experience in Data Engineering (not just analysis) Hands-on with: Python, SQL, ETL/data pipeline ...

leadership experience Strong Azure data platform expertise, including Azure Databricks Experience designing modern lakehouse and enterprise data architectures Strong understanding of data governance, metadata, MDM and enterprise data modelling Experience supporting AI/ML initiatives and modern AI data platforms Excellent stakeholder management and communication skills Experience working within enterprise ...

leadership experience Strong Azure data platform expertise, including Azure Databricks Experience designing modern lakehouse and enterprise data architectures Strong understanding of data governance, metadata, MDM and enterprise data modelling Experience supporting AI/ML initiatives and modern AI data platforms Excellent stakeholder management and communication skills Experience working within enterprise ...

Work with client business and technical teams to understand requirements and translate them into scalable cloud solutions. Establish best practices for data governance, security, metadata management, and data quality. Ensure compliance with enterprise security standards using IAM, encryption, audit logging, and networking best practices. Provide technical leadership, mentor development teams ...

across cloud-based and on-premises environments. Apply software engineering and DataOps principles to improve deployment, automation, monitoring and reliability. Support data quality, governance, metadata management and security requirements. Collaborate with technical teams and stakeholders to deliver robust data solutions that meet business and operational needs. What Were Looking ...

Root cause analysis Energy optimization Production optimization Digital worker capabilities Intelligent alarm management Autonomous operations Establish frameworks for: Data governance Data quality Asset hierarchies Metadata management Industrial data models AI model lifecycle management Responsible AI in industrial environments Support sales and growth activities by: Shaping opportunities Developing proposals Leading client ...

dashboards, APIs, data feeds, monitoring and alerting capabilities, and self-service features.Collaborate with engineering and governance teams to establish data contracts, quality rules, lineage, metadata, ownership, access controls, retention, and monitoring.Maintain and prioritize the backlog using customer value, business impact, risk, dependencies, effort, and capacity.Coordinate delivery across Data Engineering ...

reason over, and act on enterprise data (with guidance on architecture and safety). Semantic Layers & Ontologies – Contribute to semantic models (metrics, definitions, and metadata) that make it easier for business users to query data consistently. LLM‐Powered Analytics – Prototype LLM‐enabled features for summarisation, insight narration, and conversational analytics ...

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 ...