1 to 25 of 173 Metadata Jobs in the UK

data models, and data integration strategies. Ensuring data architecture solutions are secure, scalable, and high performing, adhering to enterprise standards and best practices. Leading technical efforts in data quality, metadata management, data cataloguing, and governance (including Unity Catalogue if applicable). Providing technical guidance to junior engineers and analysts in the adoption of modern data architecture patterns. Evaluating and recommending More ❯

direction of a Lloyds business, not just maintain it. Key responsibilities: Design and build Data Lake and Data Warehouse solutions Create scalable, automated batch and streaming data pipelines Optimise metadata, catalogue, lineage, and data quality processes Support business teams with data visualisation and reporting solutions Ensure secure handling of complex and sensitive data Collaborate with stakeholders across the business to More ❯

Experience with pair programming, conducting code reviews, and mentoring team members. Proven ability to reconcile data across systems and ensure data quality and integrity. Experience with data cataloging and metadata management using tools like AWS Glue Data Catalog. Demonstrated self-sufficiency in exploring new tools, troubleshooting issues, and continuously improving processes. Hands-on experience with Apache Airflow for orchestrating complex More ❯

Experience with pair programming, conducting code reviews, and mentoring team members. Proven ability to reconcile data across systems and ensure data quality and integrity. Experience with data cataloging and metadata management using tools like AWS Glue Data Catalog. Demonstrated self-sufficiency in exploring new tools, troubleshooting issues, and continuously improving processes. Hands-on experience with Apache Airflow for orchestrating complex More ❯

Experience with pair programming, conducting code reviews, and mentoring team members. Proven ability to reconcile data across systems and ensure data quality and integrity. Experience with data cataloging and metadata management using tools like AWS Glue Data Catalog. Demonstrated self-sufficiency in exploring new tools, troubleshooting issues, and continuously improving processes. Hands-on experience with Apache Airflow for orchestrating complex More ❯

Experience with pair programming, conducting code reviews, and mentoring team members. Proven ability to reconcile data across systems and ensure data quality and integrity. Experience with data cataloging and metadata management using tools like AWS Glue Data Catalog. Demonstrated self-sufficiency in exploring new tools, troubleshooting issues, and continuously improving processes. Hands-on experience with Apache Airflow for orchestrating complex More ❯

Experience with pair programming, conducting code reviews, and mentoring team members. Proven ability to reconcile data across systems and ensure data quality and integrity. Experience with data cataloging and metadata management using tools like AWS Glue Data Catalog. Demonstrated self-sufficiency in exploring new tools, troubleshooting issues, and continuously improving processes. Hands-on experience with Apache Airflow for orchestrating complex More ❯

implementing cloud data migration and storage patterns on one or more of AWS, GCP and Microsoft Azure Experience implementing and integrating data management platforms for data cataloguing, classification and metadata management. Experience designing and developing data privacy, security and entitlements frameworks for cloud provider ecosystems (AWS, Azure, GCP). Good understanding of cloud networking architecture, operations, automation and cost management. More ❯

Analytical Data Engineer Job Requirements Essential 2-5 years' experience in data modelling. Advanced level in application-based data modelling and ETL. Strong background in data analysis, cleansing, enrichment, metadata management, and data innovation. Proficiency in SQL and MySQL. Experience with business intelligence tools: Power BI, Sisense, Quicksight. Hands-on experience with ETL tools, ideally Sagemaker Unified Studio. Ability to More ❯

Analytical Data Engineer Job Requirements Essential 2-5 years' experience in data modelling. Advanced level in application-based data modelling and ETL. Strong background in data analysis, cleansing, enrichment, metadata management, and data innovation. Proficiency in SQL and MySQL. Experience with business intelligence tools: Power BI, Sisense, Quicksight. Hands-on experience with ETL tools, ideally Sagemaker Unified Studio. Ability to More ❯

medallion-based architecture, with curated dimensional models in the gold layer built for analytical use Strong understanding and or use of unity catalog alongside core databricks functionality to drive metadata management Strong understanding of cloud economics, including cost management strategies and optimising solutions for customer needs. Experience with infrastructure as code, proficiency using tools such as Terraform to automate and More ❯

physical data models to support business and technical requirements. Collaborate with data architects, analysts, and engineers to ensure accurate translation of business needs into data solutions. Maintain data dictionaries, metadata, and documentation for consistency and reusability across the organization. Optimize data models for performance, scalability, and integration with existing systems. Ensure compliance with data governance, security, and quality standards. Support More ❯

physical data models to support business and technical requirements. Collaborate with data architects, analysts, and engineers to ensure accurate translation of business needs into data solutions. Maintain data dictionaries, metadata, and documentation for consistency and reusability across the organization. Optimize data models for performance, scalability, and integration with existing systems. Ensure compliance with data governance, security, and quality standards. Support More ❯

data quality, integrity and compliance with governance policies and regulatory standards. Collaborate with enterprise architects, DBAs and infrastructure teams to optimize data performance security. Develop and maintain data lineage, metadata and architecture documentation. Support reporting and analytics initiatives by ensuring data availability and consistency across systems. Assist in designing data integration using tools such as OIC (Oracle Integration Cloud), Oracle More ❯

Spark (SQL, PySpark), Databricks Workflows Data Pipeline Design : Proven experience in scalable ETL/ELT development Azure Services : Data Lake, Blob Storage, Synapse Data Governance : Unity Catalog, access control, metadata management Performance Tuning : Partitioning, caching, Spark job optimization Cloud Architecture : Infrastructure-as-code, monitoring, automation Finance Domain Knowledge : Experience with financial systems and reporting Data Modelling : Kimball methodology, star schemas More ❯

ETL workflows.• Develop and optimise relational and non-relational database systems.• Collaborate with analysts, researchers, and IT teams to deliver tailored data solutions.• Implement and maintain data governance and metadata frameworks.• Ensure data security, integrity, and compliance with regulations such as GDPR.• Contribute to data architecture design and enterprise data strategy.• Lead technical data planning within change programmes.• Explore and More ❯

platforms, data warehousing (Snowflake), and real-time systems. Experience with data modelling standards (e.g., 3NF, Dimensional, Vault 2.0) and tools (e.g., Erwin, Lucidchart). Strong grasp of data governance, metadata management, and compliance frameworks (e.g., GDPR). Hands-on understanding of Python, SQL, and modern data engineering tools (e.g., Airflow, DBT, Atlan). Exceptional consulting and stakeholder management skills. Career More ❯

succeed You'll bring extensive experience in data engineering within Azure environments, with a strong track record in modernisation and large-scale migration projects. You'll be confident designing metadata-driven frameworks and managing Databricks environments, with hands-on expertise in Python, T-SQL, and PySpark. Your leadership and mentoring skills will be key, alongside your ability to collaborate across More ❯

DB and more Making informed decisions on the strategic direction and roadmap for the use and implementation of cloud platforms and DevOps methodologies. Design scalable and efficient data models, metadata systems, and data catalogues aligned with business objectives. Optimise performance and resolve issues to ensure data accessibility and responsiveness. Provide guidance and oversight to project teams on data architecture and More ❯

and responsive development and maintenance of flexible, quality-assured, dimensional models for use by analysts, ensuring dimensions are conformed wherever possible Developing tools to collect, store and present data, metadata, and documentation that enable people to gather and apply insights from data effectively Drawing attention to data quality and data governance issues, including issues affecting equity of services, and support More ❯

Skilled in using documentation and project tracking tools such as Jira, Confluence, or Azure DevOps. Familiarity with cloud data warehouse platforms like Snowflake and related data governance, quality, and metadata management principles. Experienced in reporting and visualization tools, including Power BI, Tableau, and Excel dashboards. We are proud to be a Disability Confident Committed employer. If you have a disability More ❯

engineers, analysts, and business stakeholders to gather and translate data requirements . E nsuring data models support operations, business intelligence and analytics use cases . I mplementing and maintaining metadata and data dictionaries . R eviewing and optimising existing data models for performance and scalability . E nsuring data models align with data governance and security standards . M entoring More ❯

Azure services such as Azure SQL Database, Data Factory, Data Lake, Cosmos DB, and more Define the strategic roadmap for cloud platforms and DevOps methodologies Build scalable data models, metadata systems, and data catalogues aligned with business goals Optimise system performance and ensure data accessibility Provide architectural guidance across the full data product lifecycle Collaborate with enterprise architects, solution architects More ❯

Azure services such as Azure SQL Database, Data Factory, Data Lake, Cosmos DB, and more Define the strategic roadmap for cloud platforms and DevOps methodologies Build scalable data models, metadata systems, and data catalogues aligned with business goals Optimise system performance and ensure data accessibility Provide architectural guidance across the full data product lifecycle Collaborate with enterprise architects, solution architects More ❯

Data Governance industry best practice is useful (such as DAMA’s DMBoK & CDMP, EDM Council’s DCAM), including but not limited to: Regulatory compliance (GDPR, CCPA) Data quality and metadata management AI data governance protocols Data lifecycle and classification Evidence, experience and understanding of data strategy, management concepts and associated business processes and tools - including Data Governance and Data Quality. More ❯