76 to 100 of 167 Metadata Management Jobs in the UK excluding London

stable batch-first integration strategy with AS400 during its .NET migration, with a roadmap toward API integration. Data Governance & Quality Implement the technical foundation for data governance quality checks, metadata management, and master data validation. Embed business rules and validation logic directly within data pipelines. Define and manage data security and access controls (Azure and Power BI row More ❯

stable “batch-first” integration strategy with AS400 during its .NET migration, with a roadmap toward API integration. Data Governance & Quality Implement the technical foundation for data governance – quality checks, metadata management, and master data validation. Embed business rules and validation logic directly within data pipelines. Define and manage data security and access controls (Azure and Power BI row More ❯

reporting and analytics needs into efficient, well-governed data models. Your leadership will be key in identifying gaps, driving improvements, and implementing best practices in dimensional modelling, normalization, and metadata management. A strong understanding of the Insurance domain—including Specialized Insurance, London Market operations, and Regulatory Data—is essential. You will apply this domain expertise to ensure that data More ❯

reporting and analytics needs into efficient, well-governed data models. Your leadership will be key in identifying gaps, driving improvements, and implementing best practices in dimensional modelling, normalization, and metadata management. A strong understanding of the Insurance domain—including Specialized Insurance, London Market operations, and Regulatory Data—is essential. You will apply this domain expertise to ensure that data More ❯

reporting and analytics needs into efficient, well-governed data models. Your leadership will be key in identifying gaps, driving improvements, and implementing best practices in dimensional modelling, normalization, and metadata management. A strong understanding of the Insurance domain—including Specialized Insurance, London Market operations, and Regulatory Data—is essential. You will apply this domain expertise to ensure that data More ❯

business stakeholders to shape and deliver the long-term vision for enterprise-grade data architecture. Key Responsibilities Design and implement scalable database solutions, conceptual and logical data models, and metadata-driven pipelines Own the full data lifecycle from initial design and ingestion to governance and performance optimisation Lead architectural direction across the platform, helping the business move from legacy … Databricks-based) Data modelling using Kimball and/or Data Vault methodology Experienced with both structured and unstructured data environments Experience with MDM, data lineage, data cataloguing, and enterprise metadata management Familiar with Agile, SCRUM, and project frameworks like PRINCE2 Requirments Proven experience as a Data Architect or Lead Data Engineer in enterprise or complex environments Strong ability More ❯

business stakeholders to shape and deliver the long-term vision for enterprise-grade data architecture. Key Responsibilities Design and implement scalable database solutions, conceptual and logical data models, and metadata-driven pipelines Own the full data lifecycle from initial design and ingestion to governance and performance optimisation Lead architectural direction across the platform, helping the business move from legacy … Databricks-based) Data modelling using Kimball and/or Data Vault methodology Experienced with both structured and unstructured data environments Experience with MDM, data lineage, data cataloguing, and enterprise metadata management Familiar with Agile, SCRUM, and project frameworks like PRINCE2 Requirments Proven experience as a Data Architect or Lead Data Engineer in enterprise or complex environments Strong ability More ❯

business stakeholders to shape and deliver the long-term vision for enterprise-grade data architecture. Key Responsibilities Design and implement scalable database solutions, conceptual and logical data models, and metadata-driven pipelines Own the full data lifecycle from initial design and ingestion to governance and performance optimisation Lead architectural direction across the platform, helping the business move from legacy … Databricks-based) Data modelling using Kimball and/or Data Vault methodology Experienced with both structured and unstructured data environments Experience with MDM, data lineage, data cataloguing, and enterprise metadata management Familiar with Agile, SCRUM, and project frameworks like PRINCE2 Requirments Proven experience as a Data Architect or Lead Data Engineer in enterprise or complex environments Strong ability More ❯

/or Scala. Expertise in ETL/ELT processes, data warehousing, and data mesh architectures. Familiarity with AI/ML concepts and their application in data analytics. Experience with metadata management, data lineage tracking, and data cataloguing. Knowledge of serverless data processing, event-driven architectures, and modern data stacks. More ❯

/or Scala. Expertise in ETL/ELT processes, data warehousing, and data mesh architectures. Familiarity with AI/ML concepts and their application in data analytics. Experience with metadata management, data lineage tracking, and data cataloguing. Knowledge of serverless data processing, event-driven architectures, and modern data stacks. More ❯

/or Scala. Expertise in ETL/ELT processes, data warehousing, and data mesh architectures. Familiarity with AI/ML concepts and their application in data analytics. Experience with metadata management, data lineage tracking, and data cataloguing. Knowledge of serverless data processing, event-driven architectures, and modern data stacks. More ❯

engineers. Excellent problem-solving skills and experience in agile environments. Desirable: Experience with streaming data (Kafka/Kinesis), Docker/Kubernetes, Terraform, CI/CD pipelines, NoSQL databases, and metadata management tools. Company Benefits: Enhanced Parental Leave Generous annual leave Healthcare Plan Annual Giving Day - an extra day to give back to yourself or your community Cycle-to More ❯

engineers. Excellent problem-solving skills and experience in agile environments. Desirable: Experience with streaming data (Kafka/Kinesis), Docker/Kubernetes, Terraform, CI/CD pipelines, NoSQL databases, and metadata management tools. Company Benefits: Enhanced Parental Leave Generous annual leave Healthcare Plan Annual Giving Day - an extra day to give back to yourself or your community Cycle-to 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 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 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 More ❯

to fulfil the strategic data needs of the organisation, as defined by chief data architects. At this role level, you will: * design, support and provide guidance for the upgrade, management, decommission and archive of data in compliance with data policy * provide input into data dictionaries * define and maintain the data technology architecture, including metadata, integration and business intelligence … architect) Level: working You can: * develop data standards for a specific component * analyse where data standards have been applied or breached, and undertake an impact analysis of that breach Metadata management Level: working You can: * work with metadata repositories to complete complex tasks such as data and systems integration impact analysis * maintain a repository to ensure information … remains accurate and up to date Problem management Level: working You can: * initiate and monitor actions to investigate patterns and trends to resolve problems * effectively consult specialists where required * determine the appropriate remedy and assist with its implementation * determine preventative measures Strategic thinking Level: awareness You can: * explain the strategic context of your work and why it is important More ❯

to fulfil the strategic data needs of the organisation, as defined by chief data architects. At this role level, you will: design, support and provide guidance for the upgrade, management, decommission and archive of data in compliance with data policy provide input into data dictionaries define and maintain the data technology architecture, including metadata, integration and business intelligence … architect) Level: working You can: develop data standards for a specific component analyse where data standards have been applied or breached, and undertake an impact analysis of that breach Metadata management Level: working You can: work with metadata repositories to complete complex tasks such as data and systems integration impact analysis maintain a repository to ensure information … remains accurate and up to date Problem management Level: working You can: initiate and monitor actions to investigate patterns and trends to resolve problems effectively consult specialists where required determine the appropriate remedy and assist with its implementation determine preventative measures Strategic thinking Level: awareness You can: explain the strategic context of your work and why it is important More ❯

alignment by engaging with leaders across domains and geographies. Ensure data engineering initiatives match evolving business priorities. Promote a product mindset, balancing technical efficiency with clear business value. Team Management Lead the Data Engineering team, providing supervision, coaching, and professional development. Work with the Data Delivery Manager to improve team productivity and velocity. Oversee planning sessions, standups, retros, and … 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 More ❯

alignment by engaging with leaders across domains and geographies. Ensure data engineering initiatives match evolving business priorities. Promote a product mindset, balancing technical efficiency with clear business value. Team Management Lead the Data Engineering team, providing supervision, coaching, and professional development. Work with the Data Delivery Manager to improve team productivity and velocity. Oversee planning sessions, standups, retros, and … 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 More ❯

alignment by engaging with leaders across domains and geographies. Ensure data engineering initiatives match evolving business priorities. Promote a product mindset, balancing technical efficiency with clear business value. Team Management Lead the Data Engineering team, providing supervision, coaching, and professional development. Work with the Data Delivery Manager to improve team productivity and velocity. Oversee planning sessions, standups, retros, and … 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 More ❯

integration patterns, ETL/ELT processes, and data pipeline orchestration. Experience with AWS data platforms and their respective data services. Solid understanding of data governance principles, including data quality, metadata management, and access control. Familiarity with big data technologies (e.g., Spark, Hadoop) and distributed computing. Proficiency in SQL and at least one programming language (e.g., Python, Java More ❯

integration patterns, ETL/ELT processes, and data pipeline orchestration. Experience with AWS data platforms and their respective data services. Solid understanding of data governance principles, including data quality, metadata management, and access control. Familiarity with big data technologies (e.g., Spark, Hadoop) and distributed computing. Proficiency in SQL and at least one programming language (e.g., Python, Java More ❯

integration patterns, ETL/ELT processes, and data pipeline orchestration. Experience with AWS data platforms and their respective data services. Solid understanding of data governance principles, including data quality, metadata management, and access control. Familiarity with big data technologies (e.g., Spark, Hadoop) and distributed computing. Proficiency in SQL and at least one programming language (e.g., Python, Java More ❯

integration patterns, ETL/ELT processes, and data pipeline orchestration. Experience with AWS data platforms and their respective data services. Solid understanding of data governance principles, including data quality, metadata management, and access control. Familiarity with big data technologies (e.g., Spark, Hadoop) and distributed computing. Proficiency in SQL and at least one programming language (e.g., Python, Java More ❯