5 of 5 Permanent Metadata Management Jobs in the Thames Valley

monitoring tools, BI and Data Warehousing solutions and ETL and migration technologies \n A thorough understanding of one or more from: Master Data Management, Data Lineage analysis, Metadata Management, Data Quality assessment and management, Data Transformation and migration \n Ability to apply advanced analytics and statistics ...

logging and monitoring tools, BI and Data Warehousing solutions and ETL and migration technologies\ NA thorough understanding of one or more from: Master Data Management, Data Lineage analysis, Metadata Management, Data Quality assessment and management, Data Transformation and migration\ NAbility to apply advanced analytics and statistics ...

Databricks and related services. Develop and maintain datasets and data models that support analytics and reporting, following established modelling standards Contribute to data lineage, metadata management and cataloguing practices, including exposure to Purview Work closely with the Lead Data Engineer, Analysts and Architects to develop and improve engineering ...

development and implementation of the company's Data Governance Framework Establish and improve Data Governance policies, controls and standards Drive improvements in Data Quality Management and wider Data Governance processes Implement Data Ownership and Data Stewardship frameworks across the business Work closely with Data, Technology and Analytics teams … wider Data Governance initiatives Develop strong Metadata Management and improve visibility across enterprise data assets Support wider Data Governance strategy and long-term business transformation projects Manage a team and help build out the wider Data Governance capability Engage senior stakeholders to ensure strong adoption of Data Governance ...

leading governance forums, stewardship communities and decision-making structures. Embedding governance controls within Microsoft Fabric and Microsoft Purview, including cataloguing, lineage, classification and metadata management. Driving enterprise data quality management, issue remediation and continuous improvement. Leading Responsible AI governance, including model oversight, transparency, explainability and monitoring. Defining governance … culture where: Business capabilities are aligned to clear data domains and ownership models. Critical business data is trusted, well-defined and fit for purpose. Metadata, lineage and classifications are visible and actively maintained. Data quality issues are identified, managed and resolved through accountable ownership. AI solutions are governed responsibly ...