1 to 25 of 115 Metadata Management Jobs in the UK

promote the value of data across business and technology teams. Mentor data engineers, BI developers, and other stakeholders in data architecture and best practices. Maintain comprehensive architecture documentation for metadata, data lineage, and data governance. Essential Skills & Qualifications Extensive experience architecting enterprise data solutions and designing scalable data platforms. Proven expertise in data modeling (conceptual, logical, physical), metadata management, and master data management (MDM). Deep understanding of data integration, transformation, and ingestion techniques using modern tools (e.g., Azure Data Factory, Boomi, Informatica, Talend, dbt, Apache NiFi). Strong familiarity with data warehousing, data lake/lakehouse architectures, and cloud-native analytics platforms. Hands-on experience with SQL and cloud data platforms (e.g., Snowflake, Azure … tools (e.g., Power BI, Tableau) and data visualization best practices. Strong knowledge of data governance, data privacy, and compliance frameworks (e.g., GDPR, ISO 27001). Excellent communication and stakeholder management skills; able to translate complex data concepts into business-friendly language. Ability to lead technical discussions and influence data-driven decision making across teams. Certifications such as Microsoft Certified More ❯

solutions. Collaborate with IT teams to ensure data infrastructure is optimized for performance, scalability, and reliability. Provide leadership and mentorship to data architecture and engineering teams. Data Integration and Management: Design and implement robust ETL processes to integrate data from various sources into the data warehouse and big data platforms. Oversee the management of metadata, master data More ❯

driver of public spending. We collaborate with and directly support departments to deliver the Government Finance Function strategy, building finance, debt and risk capability across government and developing the management information, tools, and frameworks to better understand and ensure value for money. The Group is committed to being an excellent place to work, with a relentless focus on good … management, learning and development and continuous improvement in everything we do. About the Team The Strategy, Performance & Improvement (SPI) Team is one of the central Government Finance Function (GFF) teams supporting over 9,000 finance colleagues across government. We set the Finance Standard (GovS006), monitor performance, and maintain a central library of best practice—the NOVA Functional Reference Model … and engage with, support and lead on the finance data requirements and design for any future systems required for central financial reporting within Government and HM Treasury. Showcase excellent metadata quality management and embed effective processes and procedures in product lifecycles to drive high quality outputs and standards, utilising Project, and Programme Management methodologies, best practices, and More ❯

with evolving data governance standards. Key Responsibilities Architect Scalable Data Solutions: Design and implement efficient data models and database architectures to support current and future business needs. Develop Documentation & Metadata Standards: Maintain clear and up-to-date architectural documentation, including metadata definitions and data lineage diagrams. Establish Data Standards & Best Practices: Define and enforce data architecture principles, governance … Azure-based machine learning workflows and Databricks on Azure Designing and optimizing data lakes, warehouses, and pipelines Experience implementing data governance, security standards, and compliance practices. Strong understanding of metadata management, data lineage, and data quality frameworks. Preferred Skills & Knowledge: Familiarity with big data technologies such as Hadoop, Spark, or Kafka Excellent communication skills with the ability to … strategies to non-technical stakeholders. Outstanding problem-solving abilities and organizational skills. Certifications (Preferred/Desirable): Azure Solutions Architect Expert Azure Data Engineer Associate Knowledge of Azure security & access management (Azure AD, Azure Policy) Experience with Azure DevOps and CI/CD practices More ❯

and data governance Implement data quality monitoring and alerting processes. Work with data governance teams to ensure compliance with data governance policies and standards. Implement data lineage tracking and metadata management processes. Collaboration & Communication: Collaborate closely with data scientists, economists, and other technical teams to understand data requirements and translate them into technical solutions. Communicate technical concepts effectively More ❯

and data governance Implement data quality monitoring and alerting processes. Work with data governance teams to ensure compliance with data governance policies and standards. Implement data lineage tracking and metadata management processes. Collaboration & Communication: Collaborate closely with data scientists, economists, and other technical teams to understand data requirements and translate them into technical solutions. Communicate technical concepts effectively More ❯

and data governance Implement data quality monitoring and alerting processes. Work with data governance teams to ensure compliance with data governance policies and standards. Implement data lineage tracking and metadata management processes. Collaboration & Communication: Collaborate closely with data scientists, economists, and other technical teams to understand data requirements and translate them into technical solutions. Communicate technical concepts effectively More ❯

term scalability. Reporting to the Head of Data, this role will be responsible to define and maintain data standards, data models, and data governance frameworks to enable effective data management and analytics across the organization. The ideal candidate will have strong expertise in data architecture, data modelling, and data governance, with hands-on experience in Azure Databricks and Unity … Catalog for metadata management and scalable data & analytics. Key responsibilities and primary deliverables Define and enforce enterprise data architecture principles, policies, and standards in collaboration with the Head of Data. Develop and maintain current (“as-is”) and future (“to-be”) data architecture blueprints, ensuring alignment with business needs. Design and document conceptual, logical, and physical data models, optimizing … for Azure Databricks Lakehouse implementation and Unity Catalog integration. Implement and manage data cataloguing and metadata governance using Unity Catalog to contextualise data and ensure data discoverability, lineage, and compliance. Support Head of Data to define data access, security, and sharing policies for the enterprise and work with the engineering team to implement policies within Azure Databricks environments. Work More ❯

term scalability. Reporting to the Head of Data, this role will be responsible to define and maintain data standards, data models, and data governance frameworks to enable effective data management and analytics across the organization. The ideal candidate will have strong expertise in data architecture, data modelling, and data governance, with hands-on experience in Azure Databricks and Unity … Catalog for metadata management and scalable data & analytics. Key responsibilities and primary deliverables Define and enforce enterprise data architecture principles, policies, and standards in collaboration with the Head of Data. Develop and maintain current (“as-is”) and future (“to-be”) data architecture blueprints, ensuring alignment with business needs. Design and document conceptual, logical, and physical data models, optimizing … for Azure Databricks Lakehouse implementation and Unity Catalog integration. Implement and manage data cataloguing and metadata governance using Unity Catalog to contextualise data and ensure data discoverability, lineage, and compliance. Support Head of Data to define data access, security, and sharing policies for the enterprise and work with the engineering team to implement policies within Azure Databricks environments. Work More ❯

cycle, supports them in becoming truly data-driven, and in turn solves complex industry challenges faced across a variety of sectors. Here, you will become a specialist in data management, with projects spanning data governance, data ethics, data quality and data architecture, through managing and delivering work streams that expose the true value of clients' data. Additionally, you'll … are keen to strengthen their team and hear from you. Get a head start on the competition, and apply here today. What You Need: Solid professional grounding in 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 clients Company: Graduate Recruitment Bureau (Hiring for client) Location: London, UK Salary Notes: £55-70K Course Notes: Any considered with a preference for STEM subjects Jobs related More ❯

term scalability. Reporting to the Head of Data, this role will be responsible to define and maintain data standards, data models, and data governance frameworks to enable effective data management and analytics across the organisation. The ideal candidate will have strong expertise in data architecture, data modelling, and data governance, with hands-on experience in Azure Databricks and Unity … Catalog for metadata management and scalable data & analytics. Key responsibilities Define and enforce enterprise data architecture principles, policies, and standards in collaboration with the Head of Data. Develop and maintain current (as-is) and future (to-be) data architecture blueprints, ensuring alignment with business needs. Design and document conceptual, logical, and physical data models, optimizing for Azure Databricks … Lakehouse implementation and Unity Catalog integration. Implement and manage data cataloguing and metadata governance using Unity Catalog to contextualise data and ensure data discoverability, lineage, and compliance. Support Head of Data to define data access, security, and sharing policies for the enterprise and work with the engineering team to implement policies within Azure Databricks environments. Work closely with business More ❯

designing scalable, high-performance data architectures on Azure and Databricks ? Do you thrive on solving complex data challenges, integrating modern data platforms, and defining best practices for enterprise data management? We are looking for a Data Architect to lead the design and implementation of cutting-edge data solutions in a cloud-native environment. You will play a key role … in shaping data strategy, designing high-level and low-level architectures , and ensuring the seamless integration of data management tools. If you enjoy working with big data technologies, governance frameworks, and modern analytics platforms , this role is for you! Key Responsibilities Design and architect scalable, secure, and cost-effective Azure Databricks solutions for business and analytical workloads. Translate business … into high-level and low-level solution designs , ensuring alignment with best practices. Define and implement enterprise data governance, security, and compliance strategies. Lead the integration of core data management capabilities , including: Master Data Management (MDM) solutions for single-source-of-truth data Data catalogue tools for metadata management and discovery Data governance frameworks for policy More ❯

performance data platforms in production environments. This role requires a deep understanding of modern data engineering practices, real-time processing, and cloud-native solutions. Key Responsibilities: Data Pipeline Development & Management: Design, implement, and maintain scalable and reliable data pipelines to ingest, transform, and load structured, unstructured, and real-time data feeds from diverse sources. Manage data pipelines for analytics … hybrid data storage models for unified access and processing. Data Governance & Stewardship: Implement robust data governance , access control , and stewardship policies aligned with compliance and security best practices. Establish metadata management, data lineage, and auditability across pipelines and environments. Machine Learning & Advanced Analytics Enablement: Collaborate with data scientists to prepare and serve features for ML models. Maintain awareness More ❯

performance data platforms in production environments. This role requires a deep understanding of modern data engineering practices, real-time processing, and cloud-native solutions. Key Responsibilities: Data Pipeline Development & Management: Design, implement, and maintain scalable and reliable data pipelines to ingest, transform, and load structured, unstructured, and real-time data feeds from diverse sources. Manage data pipelines for analytics … hybrid data storage models for unified access and processing. Data Governance & Stewardship: Implement robust data governance , access control , and stewardship policies aligned with compliance and security best practices. Establish metadata management, data lineage, and auditability across pipelines and environments. Machine Learning & Advanced Analytics Enablement: Collaborate with data scientists to prepare and serve features for ML models. Maintain awareness More ❯

Design and implement resilient ETL/ELT workflows using technologies such as BigQuery, Dataflow, Informatica, or IBM DataStage, supporting both real-time and batch data processing. Governance & Data Quality Management: Establish comprehensive data governance frameworks, including metadata management and quality assurance, using platforms like Unity Catalog, Alation, Profisee, or DQ Pro. Strategic Advisory & Stakeholder Engagement: Serve as More ❯

solution architects, and data product teams to gather requirements and design solutions. Provide guidance on data integration, transformation, and migration strategies. Establish and maintain enterprise data models, data dictionaries, metadata repositories, and data lineage documentation. Ensure data models comply with organizational policies and regulatory requirements. Optimize data products and their components for performance, scalability, and reliability. Evaluate and recommend … warehouse design, ETL/ELT processes, and big data technologies (e.g., Snowflake, Spark). Understanding of data governance and compliance frameworks (e.g., GDPR, HIPAA). Strong communication and stakeholder management skills. Analytical mindset with attention to detail. Leadership and mentoring abilities in data modeling best practices. Preferred Skills and Qualifications Certifications in data modeling, cloud platforms, or database technologies. … tools like GitHub Actions or similar. AWS certifications such as AWS Certified Data Engineer. Knowledge of Snowflake, SQL, Apache Airflow, and DBT. Familiarity with Atlan for data cataloging and metadata management. Understanding of iceberg tables. Who we are: We're a global business empowering local teams with exciting work that is making a difference. Our portfolio includes consulting, applications More ❯

data models, and pipelines in Snowflake and cloud platforms (AWS, Azure, or GCP). Develop and optimize scalable ELT/ETL processes using SQL and Python. Define data governance, metadata management, and security best practices. Collaborate with data engineers, analysts, product managers, and stakeholders to understand data needs and translate them into robust architectural solutions. Oversee data quality More ❯

data models, and pipelines in Snowflake and cloud platforms (AWS, Azure, or GCP). Develop and optimize scalable ELT/ETL processes using SQL and Python. Define data governance, metadata management, and security best practices. Collaborate with data engineers, analysts, product managers, and stakeholders to understand data needs and translate them into robust architectural solutions. Oversee data quality More ❯

and build CI/CD pipelines using Azure DevOps to automate deployment and monitoring of data solutions to all environments. Provide knowledge sharing to data operations teams on release management and maintenance. Manage platform administration, ensuring optimal performance, availability, and scalability of Azure data services. Implement end-to-end data pipelines, ensuring data quality, data integrity and data security. … control (RBAC), encryption, and compliance with industry standards. Collaborate with data scientists, analysts, and business stakeholders to deliver high-quality data solutions. Monitor and optimize Databricks performance, including cost management guidance and cluster tuning. Stay up to date with Azure cloud innovations and recommend improvements to existing architectures. Assist data analysts with technical input. You may also be required … 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 More ❯

of data warehousing, data lakes, and enterprise data architecture. Proficiency in SQL and experience working with cloud data platforms (e.g., Azure, AWS, GCP). Familiarity with data governance frameworks, metadata management, and data cataloging tools. Excellent communication and documentation skills, with the ability to explain complex data concepts to non-technical stakeholders. Preferred Skills: Experience with insurance platforms More ❯

. Essential: 7+ years in Data Engineering, with 2+ years in a Principal or Lead role. Proven experience designing and delivering enterprise data strategies . Exceptional communication and stakeholder management skills. Expertise in enterprise-grade data warehouses (Snowflake, BigQuery, Redshift). Hands-on experience with Apache Airflow (or similar orchestration tools). Strong proficiency in Python and SQL for … pipeline development. Deep understanding of data architecture, dimensional modelling, and metadata management. Experience with cloud platforms (AWS, GCP, or Azure). Familiarity with version control, CI/CD , and Infrastructure-as-Code (Terraform or similar). Desirable: Background in fintech or payments. Knowledge of streaming frameworks (Kafka, Kinesis). Experience with dbt and data quality frameworks (e.g., Great Expectations More ❯

. Essential: 7+ years in Data Engineering, with 2+ years in a Principal or Lead role. Proven experience designing and delivering enterprise data strategies . Exceptional communication and stakeholder management skills. Expertise in enterprise-grade data warehouses (Snowflake, BigQuery, Redshift). Hands-on experience with Apache Airflow (or similar orchestration tools). Strong proficiency in Python and SQL for … pipeline development. Deep understanding of data architecture, dimensional modelling, and metadata management. Experience with cloud platforms (AWS, GCP, or Azure). Familiarity with version control, CI/CD , and Infrastructure-as-Code (Terraform or similar). Desirable: Background in fintech or payments. Knowledge of streaming frameworks (Kafka, Kinesis). Experience with dbt and data quality frameworks (e.g., Great Expectations More ❯

. Essential: 7+ years in Data Engineering, with 2+ years in a Principal or Lead role. Proven experience designing and delivering enterprise data strategies . Exceptional communication and stakeholder management skills. Expertise in enterprise-grade data warehouses (Snowflake, BigQuery, Redshift). Hands-on experience with Apache Airflow (or similar orchestration tools). Strong proficiency in Python and SQL for … pipeline development. Deep understanding of data architecture, dimensional modelling, and metadata management. Experience with cloud platforms (AWS, GCP, or Azure). Familiarity with version control, CI/CD , and Infrastructure-as-Code (Terraform or similar). Desirable: Background in fintech or payments. Knowledge of streaming frameworks (Kafka, Kinesis). Experience with dbt and data quality frameworks (e.g., Great Expectations More ❯

. Essential: 7+ years in Data Engineering, with 2+ years in a Principal or Lead role. Proven experience designing and delivering enterprise data strategies . Exceptional communication and stakeholder management skills. Expertise in enterprise-grade data warehouses (Snowflake, BigQuery, Redshift). Hands-on experience with Apache Airflow (or similar orchestration tools). Strong proficiency in Python and SQL for … pipeline development. Deep understanding of data architecture, dimensional modelling, and metadata management. Experience with cloud platforms (AWS, GCP, or Azure). Familiarity with version control, CI/CD , and Infrastructure-as-Code (Terraform or similar). Desirable: Background in fintech or payments. Knowledge of streaming frameworks (Kafka, Kinesis). Experience with dbt and data quality frameworks (e.g., Great Expectations 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 More ❯