1 to 25 of 247 Permanent Metadata Jobs in England

managing large-scale data solutions on Microsoft Azure. Unity Catalog Mastery: In-depth knowledge of setting up, configuring, and utilizing Unity Catalog for robust data governance, access control, and metadata management in a Databricks environment. Databricks Proficiency: Demonstrated ability to optimize and tune Databricks notebooks and workflows to maximize performance and efficiency. Experience with performance troubleshooting and best practices for More ❯

technologies Troubleshooting and resolving data-related issues. Architect scalable data solutions to support advanced analytics, machine learning, and real-time processing needs. Design and implement data governance frameworks, including metadata management, lineage tracking, and cataloging. Ensuring data quality and reliability; ensuring data security and compliance, including GDPR. Document data engineering standards, design decisions, and infrastructure setup for operational transparency. Collaborating More ❯

APIs, and machine learning models in coordination with DevOps teams. Define and embed best practices for data warehousing and Lakehouse architecture (e.g. Medallion). Standardise data development, modelling, and metadata management across the enterprise. Implement lineage tracking and orchestration tools to improve transparency and governance. Conduct code reviews, testing, and documentation to ensure quality and robustness of analytics outputs. Take More ❯

Governance and Quality Assurance: Embed governance, security, and data quality practices into engineering workflows. Define guardrails and reference implementations for data access control, data lineage, and compliance. Promote consistent metadata management and enforce technical standards to ensure trust in data assets. Stakeholder Engagement: Collaborate with PN D&A leadership, PN product owners, and segment D&A leadership to synchronize and More ❯

Governance and Quality Assurance: Embed governance, security, and data quality practices into engineering workflows. Define guardrails and reference implementations for data access control, data lineage, and compliance. Promote consistent metadata management and enforce technical standards to ensure trust in data assets. Stakeholder Engagement: Collaborate with PN D&A leadership, PN product owners, and segment D&A leadership to synchronize and More ❯

data from SAP (e.g., S/4HANA, BW/4HANA) and non-SAP sources (e.g., cloud platforms, APIs, third-party systems). Establish and enforce data governance policies including metadata management, data lineage tracking, and access control to ensure data integrity and compliance. Optimize data pipelines and transformation logic using SAP Datasphere's capabilities to support real-time and batch More ❯

principles of data modelling • Re-engineer data pipelines to be scalable, robust, automatable, and repeatable • Navigate, explore and query large scale datasets • Build processes supporting data transformation, data structures, metadata, dependency and workload management • Identify and resolve data issues including data quality, data mapping, database and application issues • Implement data flows to connect operational systems, data for analytics and business More ❯

conceptual, logical and physical data models to provide structured view of data domains, entities, and their relationships. Data Documentation: Create and update data dictionaries, entity-relationship diagrams (ERDs), and metadata to ensure clarity and consistency. Stakeholder Collaboration: Collaborate closely with business stakeholders to understand data requirements and translate them into structured data models that meet business needs. Data Governance Alignment More ❯

conceptual, logical and physical data models to provide structured view of data domains, entities, and their relationships. Data Documentation: Create and update data dictionaries, entity-relationship diagrams (ERDs), and metadata to ensure clarity and consistency. Stakeholder Collaboration: Collaborate closely with business stakeholders to understand data requirements and translate them into structured data models that meet business needs. Data Governance Alignment More ❯

monitoring, and documentation. Exposure to Data Modelling and Warehousing would beneficial as you will need to build data models or migrate existing ones. Drive best practices in data governance , metadata management , and data security . Contribute to the continuous improvement of our data platform and tooling. Required Skills & Experience 35 + years of experience as a Data Analyst , preferably in More ❯

skills. Preferred Qualifications: Cloud certification (Azure Data Engineer, AWS Certified Database Specialty, etc.). Familiarity with NoSQL or NewSQL databases (MongoDB, Cassandra). Experience with data governance, MDM, and metadata management tools. Working knowledge of DevOps tools (Terraform, Git, Jenkins). More ❯

data integration initiatives, orchestrating data ingestion from SAP (e.g., S/4HANA, BWS/4HANA) and non-SAP sources (e.g., cloud platforms, APIs). Establish data governance policies including metadata management, data lineage, and access control to ensure data integrity and compliance. Optimize data pipelines and transformation logic to support real-time and batch processing. Collaborate with business and technical More ❯

data environments. Design and implement complex data models supporting operational and analytical use cases. Lead data integration initiatives from SAP and non-SAP sources. Establish data governance policies, including metadata management and access control. Optimize data pipelines for real-time and batch processing. Collaborate with teams to develop robust data products and services. Monitor and tune system performance for high More ❯

into technical specifications and ensure timely delivery of data products. 4. Data Quality & Governance Implement monitoring systems to ensure data accuracy, completeness, and timeliness. Support data governance initiatives, including metadata management, lineage tracking, and access controls. Ensure compliance with regulatory standards (e.g., REMIT, EMIR) and internal audit requirements. 5. Innovation & Continuous Improvement Evaluate and adopt new technologies (e.g., streaming platforms More ❯

Administer Microsoft Fabric Lakehouse and Azure services Optimise performance across queries, datasets, and pipelines Apply data validation, cleansing, and standardisation rules Document pipeline logic and contribute to business-wide metadata catalogues Collaborate with BI, Change, and Product teams to align data outputs to needs Support groundwork for future data science and machine learning initiatives The successful applicant will be proficient More ❯

Design, implement, and support a platform providing secured access to large datasets. • Interface with tax, finance and accounting customers, gathering requirements and delivering complete BI solutions. • Model data and metadata to support ad-hoc and pre-built reporting. • Own the design, development, and maintenance of ongoing metrics, reports, analyses, dashboards, etc. to drive key business decisions. • Recognize and adopt best More ❯

with Agile/Scrum methodology, including sprint planning and backlog management. Excellent communication and stakeholder management skills. Experience with data governance operating models, data management subject areas (such as metadata management, data quality, record management, data privacy) and tools is a strong plus. Understanding of project management principles, a proactive mindset, and keen attention to detail. What we can offer More ❯

engagement, and ensure alignment across business, IT, compliance, and security teams. Establish data quality metrics, rules, and monitoring mechanisms across cloud data pipelines and lakehouses. Champion the use of metadata management, data catalogs (e.g., Azure Purview, Unity Catalog), and standardized business glossaries. Provide governance oversight for data sharing and consumption in Databricks notebooks, Power BI reports, and machine learning workflows. More ❯

data management, covering one or more of the following areas: Data governance Data ethics Data modelling Data architecture Data quality Master data management Experience of data lineage, taxonomies and metadata management Strong problem solving and analytical thinking ability, in order to adapt to different client projects and scenarios Excellent written and verbal communication skills that allow you build credibility with More ❯

They offer a structured and professional environment, providing employees with opportunities to contribute to impactful projects in a collaborative setting. Job Description Deep expertise in data governance, data quality, metadata management, profiling, analysis, and related data management tools. Lead the implementation of data governance across Risk and Finance domains, ensuring alignment with BCBS239 regulatory standards. Accountable for end-to-end More ❯

discovery, evaluating source systems and APIs, and creating stories for implementation Collaborate with third parties to ensure interoperability and integration compatibility Champion best practices in warehousing techniques (e.g. Kimball), metadata management, and performance optimisation Support delivery through integration testing, reconciliation, and reporting visualisation (e.g. Power BI, Tableau) About You: Proven experience designing data architectures for large-scale platforms and diverse More ❯

discovery, evaluating source systems and APIs, and creating stories for implementation Collaborate with third parties to ensure interoperability and integration compatibility Champion best practices in warehousing techniques (e.g. Kimball), metadata management, and performance optimisation Support delivery through integration testing, reconciliation, and reporting visualisation (e.g. Power BI, Tableau) About You: Proven experience designing data architectures for large-scale platforms and diverse More ❯

discovery, evaluating source systems and APIs, and creating stories for implementation Collaborate with third parties to ensure interoperability and integration compatibility Champion best practices in warehousing techniques (e.g. Kimball), metadata management, and performance optimisation Support delivery through integration testing, reconciliation, and reporting visualisation (e.g. Power BI, Tableau) About You: Proven experience designing data architectures for large-scale platforms and diverse More ❯

discovery, evaluating source systems and APIs, and creating stories for implementation Collaborate with third parties to ensure interoperability and integration compatibility Champion best practices in warehousing techniques (e.g. Kimball), metadata management, and performance optimisation Support delivery through integration testing, reconciliation, and reporting visualisation (e.g. Power BI, Tableau) About You: Proven experience designing data architectures for large-scale platforms and diverse More ❯

discovery, evaluating source systems and APIs, and creating stories for implementation Collaborate with third parties to ensure interoperability and integration compatibility Champion best practices in warehousing techniques (e.g. Kimball), metadata management, and performance optimisation Support delivery through integration testing, reconciliation, and reporting visualisation (e.g. Power BI, Tableau) About You: Proven experience designing data architectures for large-scale platforms and diverse More ❯