1 to 25 of 132 Metadata Jobs in London

Databricks Certified, AWS/Azure/GCP Data Engineering certifications) Experience with DataOps, CI/CD practices, and infrastructure-as-code Knowledge of data governance, data quality frameworks, and metadata management Benefits: Hybrid/remote working environment, allowing you a flexible work-life balance to thrive both in the office and from the comfort of your home Competitive compensation package More ❯

knowledge of SQL, Python, and relevant data engineering frameworks (e.g. Databricks, Synapse, Snowflake, Redshift). Experience designing data platforms leveraging PaaS and SaaS solutions. Solid understanding of information governance, metadata management, and master data management principles. Experience leading data design across full project lifecycles (Discovery, Alpha, Beta, Live). Strong understanding of API design, event-driven architecture, and microservices principles. More ❯

operational leads, and other stakeholders, coaching and supporting a data-driven culture, including KPI definition and reporting frameworks. Accountable for data extraction, transforming JSON & XML, utlising high experience within metadata management. Collaborate with data engineers to develop data, enrich product design and integrate data for predictive models or machine learning. Deliver well-defined, transformed, tested, documented, and code-reviewed datasets More ❯

operational leads, and other stakeholders, coaching and supporting a data-driven culture, including KPI definition and reporting frameworks. Accountable for data extraction, transforming JSON & XML, utlising high experience within metadata management. Collaborate with data engineers to develop data, enrich product design and integrate data for predictive models or machine learning. Deliver well-defined, transformed, tested, documented, and code-reviewed datasets 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 to both 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 to both More ❯

roadmaps, and innovation. ETL/ELT & Data Engineering – Provide oversight on robust data pipeline and integration designs using SSIS, ADF, Informatica, or IBM DataStage. Data Governance & Quality – Define governance, metadata, and quality frameworks using tools such as Unity Catalog, Profisee, Alation, or DQ Pro. Technical Leadership – Mentor cross-functional teams and embed best practices and innovation across projects. Industry Insight More ❯

roadmaps, and innovation. ETL/ELT & Data Engineering – Provide oversight on robust data pipeline and integration designs using SSIS, ADF, Informatica, or IBM DataStage. Data Governance & Quality – Define governance, metadata, and quality frameworks using tools such as Unity Catalog, Profisee, Alation, or DQ Pro. Technical Leadership – Mentor cross-functional teams and embed best practices and innovation across projects. Industry Insight More ❯

non-technical stakeholders. Nice to Have: • Experience in energy or financial trading environments. • Familiarity with cloud-based data platforms (e.g. Databricks, Snowflake). • Knowledge of data governance, lineage, and metadata management. • Exposure to data cataloguing tools and data quality frameworks. More ❯

vendor evaluation, implementation, and adoption across the enterprise. Establish and maintain reference data management frameworks and governance processes. Develop and execute data strategies, including future state architecture, data governance, metadata management, data privacy, reference data management, and data integration. Lead the design and review of data architectures for both operational platforms (APIs, event streams, transactional systems) and analytical platforms (data More ❯

to collaborate across teams. Preferred Qualifications Experience with Databricks Unity Catalog and Delta Live Tables. Familiarity with streaming frameworks (Structured Streaming, Kafka, etc.). Background in data observability and metadata management. Exposure to machine learning pipelines or MLflow within Databricks. Knowledge of infrastructure as code (IaC) using Terraform or similar tools. To apply for this role please email across your More ❯

to collaborate across teams. Preferred Qualifications Experience with Databricks Unity Catalog and Delta Live Tables. Familiarity with streaming frameworks (Structured Streaming, Kafka, etc.). Background in data observability and metadata management. Exposure to machine learning pipelines or MLflow within Databricks. Knowledge of infrastructure as code (IaC) using Terraform or similar tools. To apply for this role please email across your More ❯

Lead the design and implementation of data models, pipelines, and integration frameworks. Support the implementation of Customer Data Platforms (CDPs), MDM, and CRM systems. Ensure compliance with data governance, metadata standards, and data quality frameworks. Collaborate with stakeholders to define data architecture vision and roadmap. Contribute to the development of reusable architecture assets and design patterns. Mentor junior team members More ❯

Development Design and implement a robust data governance framework, including policies, standards, and procedures. Define data ownership models and appoint data stewards across key domains. Introduce and manage a metadata catalogue to enhance data discoverability and transparency. Establish clear retention, access, and usage policies for various data types. Governance Leadership Set up and lead a Data Governance Council to oversee More ❯

Development Design and implement a robust data governance framework, including policies, standards, and procedures. Define data ownership models and appoint data stewards across key domains. Introduce and manage a metadata catalogue to enhance data discoverability and transparency. Establish clear retention, access, and usage policies for various data types. Governance Leadership Set up and lead a Data Governance Council to oversee More ❯

data modelling, governance, and architecture best practices . Excellent leadership, communication, and stakeholder management skills. NICE TO HAVE: Background in data management, engineering, or database administration . Experience with metadata management and master data management (MDM) tools. Understanding of data governance frameworks and compliance standards. Familiarity with machine learning pipelines or AI model integration. A proactive, detail-oriented approach and More ❯

data modelling, governance, and architecture best practices . Excellent leadership, communication, and stakeholder management skills. NICE TO HAVE: Background in data management, engineering, or database administration . Experience with metadata management and master data management (MDM) tools. Understanding of data governance frameworks and compliance standards. Familiarity with machine learning pipelines or AI model integration. A proactive, detail-oriented approach and More ❯

e.g., Git, Azure DevOps). Desirable Exposure to Python or Scala for data engineering tasks. Knowledge of Power BI or other visualisation tools. Experience with data governance frameworks and metadata management. If you’re interested, get in touch ASAP with a copy of your most recent and up-to-date CV and email me at b.forbes@tenthrevolution.com or you can More ❯

/or Scala. Expertise in ETL/ELT processes, 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 cataloguing. Knowledge of serverless data processing, event-driven architectures, and modern data stacks. More ❯

that enable scalability and cross-business alignment. Design, build, and optimise data platforms leveraging cloud-native technologies (AWS, Azure, or GCP). Integrate key data management capabilities, including governance, metadata, privacy, and cataloguing. Act as a trusted advisor, translating complex technical concepts into clear business outcomes. Required Skills and Experience 10+ years of professional experience in data architecture, engineering, or More ❯

In-depth knowledge of database design, structures, and data mining techniques. Skilled in Kimball methodology and Data Vault modelling approaches. Strong understanding of database fundamentals and practical experience designing metadata-driven ingestion and transformation pipelines. Hands-on experience with Master Data Management (MDM), data cataloguing, and data lineage tracking. Advanced proficiency with Microsoft Azure data services, including Databricks, Azure Data More ❯

Lambda, Kinesis, Athena, Lake Formation. Strong hands-on experience with Snowflake - architecture, performance tuning, security, and data sharing features. Proficient in data modelling, data integration (ETL/ELT), and metadata management. Deep understanding of data governance, data security, and compliance in cloud environments. Experience with infrastructure-as-code tools (e.g., Terraform, CloudFormation) is a plus. Strong communication and stakeholder management More ❯

technical decisions with business goals. Preferred Qualifications: Experience with data product thinking or data mesh principles. Background in product architecture or enterprise architecture. Knowledge of data cataloging, lineage, and metadata management tools (e.g., Collibra, Alation, Amundsen). Familiarity with DevOps and DataOps practices, including CI/CD, version control, and infrastructure as code (e.g., Terraform). Understanding of regulatory frameworks 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 ❯

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 visualisation. More ❯