1 to 25 of 233 Permanent 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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯