1 to 25 of 41 Remote Metadata Jobs in London

workflow/orchestration tools (e.g., Airflow, Dagster, Prefect). Cloud-based Data Services: Exposure to cloud-based data services (GCP preferred; AWS/Azure also considered). Data Lineage & Metadata Management: Understanding of best practices. Data Governance & Compliance: Awareness of data governance and compliance principles (GDPR, ISO27001). SaaS/API-driven Environments: Background in SaaS/API-driven environments 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 ❯

complex, multi-system environments. Experience mapping data flows and lineage across transactional systems, integrations, and reporting platforms. Strong understanding of data management practices: data quality, master data, reference data, metadata, retention, and ownership. Hands-on exposure to at least one modern data and analytics platform (e.g. Azure Data Platform, SQL Server, Oracle, Snowflake, SAP BW/HANA, or similar). More ❯

cost efficiency. Implement best practices for data quality, error handling, automation, and monitoring. Manage data security and governance, including Row-Level Security (RLS) and compliance standards. Maintain documentation and metadata for data assets and pipeline architecture. Collaborate with analysts, data scientists, and stakeholders to deliver trusted data products. Provide technical support and troubleshoot production issues. Contribute to improving data engineering More ❯

cost efficiency. Implement best practices for data quality, error handling, automation, and monitoring. Manage data security and governance, including Row-Level Security (RLS) and compliance standards. Maintain documentation and metadata for data assets and pipeline architecture. Collaborate with analysts, data scientists, and stakeholders to deliver trusted data products. Provide technical support and troubleshoot production issues. Contribute to improving data engineering 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 ❯

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 ❯

and CI/CD for data pipelines. BI/Visualisation: Familiarity with BI and visualisation tools such as Tableau, QuickSight, or similar. Data Governance Tools: Experience with data cataloguing, metadata management, and data lineage tools. Contextual Understanding: Passionate about data quality, governance, and understanding the business context behind the data. This role is London-based and operates on a hybrid More ❯

and CI/CD for data pipelines. BI/Visualisation: Familiarity with BI and visualisation tools such as Tableau, QuickSight, or similar. Data Governance Tools: Experience with data cataloguing, metadata management, and data lineage tools. Contextual Understanding: Passionate about data quality, governance, and understanding the business context behind the data. This role is London-based and operates on a hybrid More ❯

principles. Proficiency in SQL and Python for data transformation and automation. Experience working with version control (e.g., Git) and CI/CD for data solutions. Familiarity with data governance, metadata management, and data security best practices. Excellent problem-solving, communication, and collaboration skills. Organisation: Initial Contract - 3-6 months Day Rate - Outside IR35 London (Hybrid working) Robert Half Ltd acts More ❯

engineering field. You'll Work With Azure Data Services: Data Factory, Data Lake, SQL Databricks: Spark, Delta Lake Power BI: Advanced dashboards and analytics ETL & Data Modelling: T-SQL, metadata-driven pipelines Design and implement scalable Azure-based data solutions Build and optimise data pipelines for integration and transformation Develop Power BI dashboards for global stakeholders Ensure data quality, governance More ❯

engineering field. You'll Work With Azure Data Services: Data Factory, Data Lake, SQL Databricks: Spark, Delta Lake Power BI: Advanced dashboards and analytics ETL & Data Modelling: T-SQL, metadata-driven pipelines Design and implement scalable Azure-based data solutions Build and optimise data pipelines for integration and transformation Develop Power BI dashboards for global stakeholders Ensure data quality, governance More ❯

of your field. What You'll Work With Azure Data Services: Data Factory, Data Lake, SQL Databricks: Spark, Delta Lake Power BI: Advanced dashboards ETL & Data Modelling: T-SQL, metadata-driven pipelines What you'll do Design and implement scalable Azure-based data solutions Build and optimise data pipelines for integration and transformation Develop Power BI dashboards for global stakeholders More ❯

Contract Role: Metadata Management Specialist Location: Hybrid (London - likely 1-2 days onsite per week) Duration: 6 months IR35 Status: SDS to be determined Key Responsibilities Own and maintain interim DMO metadata management repositories Ensure metadata complies with policy standards Collaborate with data owners and stewards to populate business metadata for CDEs Work with project managers to capture technical metadata … for MITBIT initiatives Establish and execute attestation and change management processes Support documentation of data lineage where required Assist in identifying long-term and interim metadata management tools Promote standardisation, visibility, and corporate-wide adoption of metadata Hands-on involvement in all aspects of metadata management Skills & Experience Strong understanding of business and technical metadata types Significant experience in metadata More ❯

Contract Role: Metadata Management Specialist Location: Hybrid (London - likely 1-2 days onsite per week) Duration: 6 months IR35 Status: SDS to be determined Key Responsibilities Own and maintain interim DMO metadata management repositories Ensure metadata complies with policy standards Collaborate with data owners and stewards to populate business metadata for CDEs Work with project managers to capture technical metadata … for MITBIT initiatives Establish and execute attestation and change management processes Support documentation of data lineage where required Assist in identifying long-term and interim metadata management tools Promote standardisation, visibility, and corporate-wide adoption of metadata Hands-on involvement in all aspects of metadata management Skills & Experience Strong understanding of business and technical metadata types Significant experience in metadata More ❯

/ML initiatives (RAG workflows, LLMs, embeddings) Make Power BI dashboards that actually refresh when they're supposed to Implement governance that doesn't make people want to scream (metadata tagging, lineage tracking, the good stuff) Collaborate with brilliant behavioural scientists and product teams who'll challenge them in the best ways The ideal candidate will: Know their way around More ❯

Knowledge of BCBS239 principles and requirements Experience of working across multiple jurisdictions and cultures Use of industry standards and frameworks (e.g. DAMA, DCAM) Data management tooling experience or proficiency (metadata/lineage, DQ platforms, reporting solutions) SQL skills to support requirements and data analysis, ideally including both raw and aggregated data with the ability to review transformation logic Candidates will More ❯

Knowledge of BCBS239 principles and requirements Experience of working across multiple jurisdictions and cultures Use of industry standards and frameworks (e.g. DAMA, DCAM) Data management tooling experience or proficiency (metadata/lineage, DQ platforms, reporting solutions) SQL skills to support requirements and data analysis, ideally including both raw and aggregated data with the ability to review transformation logic Candidates will More ❯

relational databases, APIs, and streaming sources using best-practice patterns. Collaborate with API developers for seamless data exchange. Utilize Azure Purview for governance and quality monitoring. Implement lineage tracking, metadata management, and compliance with governance standards. Partner with data scientists, economists, and technical teams to translate requirements into solutions. Communicate effectively with technical and non-technical audiences. Participate in code More ❯

deployment approaches (e.g. cloud container services (preferred), Docker or Kubernetes) and CI/CD practices. experience working with public-facing data platforms or open data services, including data modelling, metadata, or data standards. the ability to pass security clearance, backed by the right to work in the UK About The Team Within PDS, the Data & Search Team enables data-driven More ❯

enforcement of policies for data quality, security, and compliance. Experience setting up and working with in a Data Office that defines the above policies Proficiency in data cataloguing and metadata management tools such as Collibra, Atlan, Informatica, or similar platforms. Knowledge of data lineage, stewardship, and data quality management, using relevant tools and applications to support these responsibilities. Comfortable implementing More ❯

techniques (e.g., anomaly detection, NLP, predictive analytics) to improve audit depth and efficiency. Develop and implement data and AI governance frameworks for clients, including standards for data quality, lineage, metadata, responsible AI, and regulatory compliance (e.g., PRA, FCA, EU AI Act). Assess compliance with data and AI controls , validating technical design, operational processes, and end-to-end data lifecycle … with the ability to design AI-enabled audit workflows, automated testing scripts, and continuous monitoring controls. Expert knowledge of data governance and controls , including data quality rules, lineage tracking, metadata standards, and platform-level risk management. Deep understanding of AI assurance, including model governance, algorithmic transparency, Technical experience with data and AI platforms: Snowflake, Databricks, Microsoft Purview, Collibra, Informatica, AWS More ❯

for 2026 and build infrastructures to measure LTV by acquisition source. You will also develop deep-dive reporting and insights on content consumption and support evaluation of AI-driven metadata features. Develop, maintain and evolve self-service dashboards across Tableau/Looker for O&O teams - covering traffic, content, SEO and newsletter performance. What you'll need to succeed Experience More ❯

in data modeling, semantic architecture, or ontology engineering — ideally with real-world R&D, scientific, or enterprise complexity. Expertise in designing scalable, extensible knowledge systems across structured, unstructured, and metadata-heavy environments. Demonstrated success working on data systems that integrate across multiple domains and user groups. Hands-on experience designing or implementing knowledge graphs, domain-specific schemas, or structured data More ❯