26 to 50 of 148 Metadata Jobs in England

glossaries, and implement robust data quality frameworks Identify and manage internal and external data sources, ensuring strong access and sharing controls. AI & Technology Enablement Build tools and processes for metadata management, data quality, and data sharing. Leverage AI and automation tools to improve data governance capabilities. Use Python, SQL, PySpark, Power BI, and related tools for data processing and visualization. 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 ❯

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 ❯

and equality of opportunity for all. Senior Responsibilities Taking a specific area of accountability on data ecosystem solution architecture, e.g., master data management, reference data management, enterprise data catalogue, metadata Taking a specific area of responsibility in organisation wide data policies, e.g., data privacy, data archival, data lifecycle management, data processing, data analysis Ensuring specific areas of accountability and responsibility More ❯

and innovation Technology Cloud & Data Platforms: Azure Synapse, Azure Data Lake, Azure Data Factory Data Modelling & Integration: SQL, ETL tools, data pipelines Architecture & Governance: Enterprise data models, data catalogues, metadata management Collaboration & Documentation: Agile delivery, architecture documentation, stakeholder workshops Join a business where data is at the heart of decision-making and where you can work on exciting projects that More ❯

and innovation Technology Cloud & Data Platforms: Azure Synapse, Azure Data Lake, Azure Data Factory Data Modelling & Integration: SQL, ETL tools, data pipelines Architecture & Governance: Enterprise data models, data catalogues, metadata management Collaboration & Documentation: Agile delivery, architecture documentation, stakeholder workshops Join a business where data is at the heart of decision-making and where you can work on exciting projects that 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 ❯

to at least 3NF Strong knowledge of database structure systems and data mining Proficient in Kimball methodology and Data Vaults Deep understanding of database fundamentals and experience in designing metadata-driven ingestion and transformation pipelines. Experienced in Master Data Management (MDM), data cataloguing, and managing data lineage Familiarity with accelerators and extensive knowledge of Azure Cloud Services including DataBricks, Azure More ❯

expertise with Talend and Snowflake Solid knowledge of ETL tools and data transformation techniques (JSON, XML) Proficiency in SQL, Python, or other scripting languages for automation Strong understanding of metadata structures, relational databases, and data modeling Hands-on experience with version control and CI/CD practices Excellent analytical and problem-solving skills Strong communication skills and ability to work More ❯

architecture Strong background in Data Lakes, cloud-based data warehousing (eg Snowflake), and Big Data environments Proven success delivering scalable data architecture solutions across complex programmes Deep understanding of metadata management and advanced data modelling practices Experience with various modelling methodologies (3NF, Dimensional, Data Vault) Ability to translate business requirements into long-term architectural strategies Practical knowledge of regulatory compliance More ❯

and dialogue annotation, tailored for NLP enrichments across communication products. Shape and evolve schematic structures and data models that serve as the foundation for annotation quality and reuse. Define metadata structures and enrichment tags that help interpret communication context, intent, and relevance to user queries. Collaborate with ML engineers and product stakeholders to align annotation efforts with model requirements and More ❯

Business Intelligence and analytics platforms. - Collaborate with cross-functional teams to gather requirements, define technical specifications, and deliver robust data solutions. - Define and maintain the data technology architecture, including metadata, integration and Business Intelligence or data warehouse architecture - Ensure data quality, governance, and security standards are upheld across all solutions. - Develop and deliver Risk and ingestion functionalities within the SAS More ❯

engagement. Data Management & Quality Assurance Establish data governance protocols for spatial data accuracy, completeness, and consistency. Implement ETL workflows using ArcGIS Data Interoperability tools or third-party solutions. Manage metadata standards and spatial data cataloging. Security & Access Control Configure role-based access controls and user permissions. Ensure compliance with data privacy and security standards. Implement secure data sharing protocols with More ❯

and standards to ensure data quality from source to consumption. Standardise code, product, and service quality across engineering teams by implementing best practices and governance. Design and promote reusable metadata libraries and cross-business standards in collaboration with other technical disciplines. Partner with Lead Data Engineers, Data Architects, and Technologists to design and develop innovative solutions. Continually improve data engineering More ❯

and standards to ensure data quality from source to consumption. Standardise code, product, and service quality across engineering teams by implementing best practices and governance. Design and promote reusable metadata libraries and cross-business standards in collaboration with other technical disciplines. Partner with Lead Data Engineers, Data Architects, and Technologists to design and develop innovative solutions. Continually improve data engineering More ❯

knowledge of Azure Cloud Services (DataBricks, ADF, Azure SQL, CosmosDB). Proficiency in Kimball methodology and Data Vaults. Experience with MDM, data cataloguing, and lineage management. Skilled in designing metadata-driven ingestion and transformation pipelines. Proven track record in agile delivery environments (SCRUM, PRINCE2, Lean). Excellent communication skills-able to bridge technical and non-technical audiences. Passion for emerging More ❯

knowledge of Azure Cloud Services (DataBricks, ADF, Azure SQL, CosmosDB). Proficiency in Kimball methodology and Data Vaults. Experience with MDM, data cataloguing, and lineage management. Skilled in designing metadata-driven ingestion and transformation pipelines. Proven track record in agile delivery environments (SCRUM, PRINCE2, Lean). Excellent communication skills-able to bridge technical and non-technical audiences. Passion for emerging More ❯

knowledge of Azure Cloud Services (DataBricks, ADF, Azure SQL, CosmosDB). Proficiency in Kimball methodology and Data Vaults. Experience with MDM, data cataloguing, and lineage management. Skilled in designing metadata-driven ingestion and transformation pipelines. Proven track record in agile delivery environments (SCRUM, PRINCE2, Lean). Excellent communication skills-able to bridge technical and non-technical audiences. Passion for emerging More ❯

aligning with client objectives in financial services. Build relationships at C-suite level by offering data-driven advisory on strategy, transformation roadmaps, and innovation opportunities. Define data governance frameworks, metadata management, and quality controls using a variety of platforms. Inspire and guide cross-functional global teams, ensuring best practices, knowledge sharing, and innovation are embedded in every engagement. Maintain awareness More ❯

aligning with client objectives in financial services. Build relationships at C-suite level by offering data-driven advisory on strategy, transformation roadmaps, and innovation opportunities. Define data governance frameworks, metadata management, and quality controls using a variety of platforms. Inspire and guide cross-functional global teams, ensuring best practices, knowledge sharing, and innovation are embedded in every engagement. Maintain awareness More ❯

aligning with client objectives in financial services. Build relationships at C-suite level by offering data-driven advisory on strategy, transformation roadmaps, and innovation opportunities. Define data governance frameworks, metadata management, and quality controls using a variety of platforms. Inspire and guide cross-functional global teams, ensuring best practices, knowledge sharing, and innovation are embedded in every engagement. Maintain awareness More ❯

aligning with client objectives in financial services. Build relationships at C-suite level by offering data-driven advisory on strategy, transformation roadmaps, and innovation opportunities. Define data governance frameworks, metadata management, and quality controls using a variety of platforms. Inspire and guide cross-functional global teams, ensuring best practices, knowledge sharing, and innovation are embedded in every engagement. Maintain awareness More ❯

aligning with client objectives in financial services. Build relationships at C-suite level by offering data-driven advisory on strategy, transformation roadmaps, and innovation opportunities. Define data governance frameworks, metadata management, and quality controls using a variety of platforms. Inspire and guide cross-functional global teams, ensuring best practices, knowledge sharing, and innovation are embedded in every engagement. Maintain awareness More ❯

data insights to support business operations effectively. Client Details This organisation is a large entity operating within the financial services sector. Description Strong expertise in data governance, data quality, metadata management, data profiling, analysis, and data management tools. Lead the implementation of data governance practices within the Risk and Finance domains, aligning with BCBS239 regulatory standards. Owns the end-to More ❯

on experience with RAG systems , vector databases (pgvector/FAISS/Weaviate/ES k-NN), embeddings , and hybrid search (BM25 + vectors). Strong grasp of chunking strategies , metadata, indexing, recall/precision trade-offs, reranking, and evaluation (ground-truth sets, offline/online metrics). Strong proficiency in Python (FastAPI) and React/Next.js . Solid experience with More ❯