26 to 50 of 302 Metadata Jobs in the UK

Solid understanding of database systems (SQL, NoSQL). Platform Architecture: Able to develop and implement data platform architecture (data lakes, data warehouses, data marts, metadata management) aligned with business requirements. Infrastructure Management: Able to manage and optimize cloud infrastructure (compute, storage, networking). Implement automation and orchestration tools. Key Responsibilities More ❯

documenting descriptions, intended audience, key metrics, and usage instructions. Contribute to the business-facing data catalog by logging newly created reports and ensuring proper metadata tagging. Collaborate with stakeholders to validate requirements and deliver actionable insights. Document workflows, requirements, and processes to ensure consistency and reproducibility. Begin informing database design More ❯

and real estate data-including metrics, KPIs, and market trends. Background in data modeling and data management best practices (e.g., dimensional modeling, data governance, metadata management). Ability to provide insights on complex financial data sets and collaborate with relevant stakeholders. WHAT WE OFFER: We are committed to supporting your More ❯

Business Insights Delivery, you will: Create proof of concepts and prototypes as part of the requirement gathering and specification process. Perform intermediate data profiling, metadata documentation, data lineage, data transformation rules in support of offshore development. Be responsible for the development, automating, compiling, and preparing reports, dashboards, cubes, etc. Work More ❯

Unit Testing - Experience in writing unit tests for data pipelines. Data Architecture - Knowledge or experience in implementing, Kimball style Data Warehouse. Experience in building Metadata with Azure Purview or Data Lake Gen2. Data Quality - Experience in applying Data Quality rules within Azure Data Flow Activities. Data Transformation - Extensive hands-on More ❯

Unit Testing - Experience in writing unit tests for data pipelines. Data Architecture - Knowledge or experience in implementing, Kimball style Data Warehouse. Experience in building Metadata with Azure Purview or Data Lake Gen2. Data Quality - Experience in applying Data Quality rules within Azure Data Flow Activities. Data Transformation - Extensive hands-on More ❯

Unit Testing - Experience in writing unit tests for data pipelines. Data Architecture - Knowledge or experience in implementing, Kimball style Data Warehouse. Experience in building Metadata with Azure Purview or Data Lake Gen2. Data Quality - Experience in applying Data Quality rules within Azure Data Flow Activities. Data Transformation - Extensive hands-on More ❯

Responsibilities will include: Data Create and maintain robust and scalable data pipelines to ingest, process, and transform data from various sources, ensuring data and metadata quality, accuracy, and consistency. This will include working with large and complex datasets, such as census and international data. Responsibility for implementation of data governance More ❯

Responsibilities will include: Data Create and maintain robust and scalable data pipelines to ingest, process, and transform data from various sources, ensuring data and metadata quality, accuracy, and consistency. This will include working with large and complex datasets, such as census and international data. Responsibility for implementation of data governance More ❯

of ETL/ELT, 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 cataloging. Understanding of serverless data processing, event-driven architectures, and modern data stacks. More ❯

of ETL/ELT, 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 cataloging. Understanding of serverless data processing, event-driven architectures, and modern data stacks. More ❯

Dimensional modelling methods Implement automated, reusable and efficient batch data pipelines and streaming data pipelines Work closely with Governance and Quality teams to ensure metadata, catalogue, lineage and known solutions to data issues are optimised Work closely with other data specialists and technicians in the organisation, such as Actuarial and More ❯

Dimensional modelling methods Implement automated, reusable and efficient batch data pipelines and streaming data pipelines Work closely with Governance and Quality teams to ensure metadata, catalogue, lineage and known solutions to data issues are optimised Work closely with other data specialists and technicians in the organisation, such as Actuarial and More ❯

What You'll Bring: Senior-level experience in data, analytics, or governance (financial services a plus) Strong knowledge of data governance, data quality, and metadata management Proficiency in Power BI, SQL, and Azure-based platforms (Synapse, Data Factory, Databricks) Familiarity with data regulations (GDPR, FCA) and SMCR environments Bonus points More ❯

refining processes and improving the agility and quality of delivery. Supporting the adoption and optimisation of tools such as Alation for data cataloguing and metadata management. Working closely with business and technical stakeholders to ensure our data models are of the highest quality and fit for purpose. What you'll More ❯

date and accurate documentation, including lineage, for all production solutions. Monitoring and optimising the performance of data warehouse systems. Managing data models, schemas, and metadata repositories. Maintaining operational data warehouse builds and resolving issues promptly. Ensuring adherence to agreed standards and controls for data marts and operational data stores. Leading More ❯

date and accurate documentation, including lineage, for all production solutions. Monitoring and optimising the performance of data warehouse systems. Managing data models, schemas, and metadata repositories. Maintaining operational data warehouse builds and resolving issues promptly. Ensuring adherence to agreed standards and controls for data marts and operational data stores. Leading More ❯

date and accurate documentation, including lineage, for all production solutions. Monitoring and optimising the performance of data warehouse systems. Managing data models, schemas, and metadata repositories. Maintaining operational data warehouse builds and resolving issues promptly. Ensuring adherence to agreed standards and controls for data marts and operational data stores. Leading More ❯

the ability to establish enterprise-scale data integration procedures and standards across an organization. Superior capabilities in data modeling, including cross-industry standardization and metadata management. Advanced data analysis capabilities, including complex source system analysis and data synthesis. Proficient in programming, testing, and building data engineering solutions using standards and More ❯

management of extremely large datasets. From Day 1, you will be challenged with a variety of tasks, ranging from creating datasets, reports, dashboards to metadata modeling, pipeline monitoring. You will interact with internal program and product owners, and technical teams to gather requirements, structure scalable and perform data solutions, and More ❯

and high throughput. Execute practices such as continuous integration and test driven development to enable the rapid delivery of working code. Design and build metadata driven data pipeline using Python and SQL in accordance with guidelines set by the Data Architect Ship medium to large features independently using industry standard More ❯

Agile Delivery, AI and Innovation, Business Process Mapping, Change Management, Content Syndication, Data Collection and Analysis, Digital Shelf Optimization, Growth Mindset, IT Data Management, Metadata and Taxonomy Design, Platform Strategy, Product Development, Review and Reporting, Stakeholder Engagement, Verbal and Written Communication Competencies : Cultivates Innovation, Customer Focus, Decision Quality, Drives Results More ❯

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 More ❯

discussions. Bachelor's degree in Computer Science, Information Technology, or a related field. Preferred qualifications: Expertise in configuring/customizing Collibra, data governance frameworks, metadata management, and data quality. Proficiency in SQL, databases (e.g., Oracle, SQL Server), and familiarity with data integration tools. Ability to translate business requirements into technical More ❯

creating data models and data flows in collaboration with the business and technical teams. Data Catalog: Assist in developing and maintaining data dictionaries and metadata repositories. Data Analysis: Analyze business data to identify opportunities for improvement. Stakeholder Communication: Serve as a point of contact between the data project team and More ❯