51 to 75 of 239 Metadata Jobs in London

play a key role in transforming business requirements into scalable and insightful reporting and dashboard solutions. Role The Oracle BI Consultant will design and develop OBIEE dashboards, reports, and metadata models (RPD). Translate business requirements into technical specifications and BI solutions. Write, optimise, and maintain complex SQL queries for data extraction, transformation, and analysis. Develop and manage data models More ❯

based services, particularly AWS Proven ability to manage stakeholders, their expectations and explain complex problems or solutions in a manner suitable for the audience. Knowledge of data governance and metadata management Knowledge of data security best practices and compliance requirements Success Looks Like: Safely implement controls to enable self-service of Data for other teams such as Data Scientists and More ❯

Scala, Kafka, SparkSQL, HBase, Impala, Hive and HDFS in multi-tenant environments Solid base in data technologies like warehousing, ETL, MDM, DQ, BI and analytical tools extensive experience in metadata management and data quality processes and tools Experience in full lifecycle architecture guidance Advanced analytical thinking and problem-solving skills Advanced knowledge of application, data and infrastructure architecture disciplines Understanding More ❯

tables, and scalability best practices It will also help you to have Experience establishing and enforcing data governance standards through technical architecture (not just documentation) Familiarity with data cataloging, metadata management, and observability tools A systems-thinking mindset-you understand the full data lifecycle and how to maintain integrity from source to dashboard At Booksy, we believe in the power More ❯

machine learning code to meet specific needs. Data Engineering: Ensure efficient data flow between databases and backend systems. MLOps : Automate ML workflows, focusing on testing, reproducibility, and feature/metadata storage. ML Architecture Design: Create machine learning architectures using Google Cloud tools and services. Engineering Software for Production: Build and deploy production-grade software for machine learning and data-driven More ❯

and governing data platform architectures (e.g. broad understanding of Informatica, Collibra, Ab Initio, Snowflake, Databricks) Appreciation of and interest in attaining end-to-end data skills e.g., data quality, metadata, data-mesh, data security, privacy & compliance Experience with Enterprise/platform/application (e.g. cloud/SAP)/data architecture Understanding of public and private cloud architectures Knowledge of architecture More ❯

and governing data platform architectures (e.g. broad understanding of Informatica, Collibra, Ab Initio, Snowflake, Databricks) Appreciation of and interest in attaining end-to-end data skills e.g., data quality, metadata, data-mesh, data security, privacy & compliance Experience with Enterprise/platform/application (e.g. cloud/SAP)/data architecture Understanding of public and private cloud architectures Knowledge of architecture More ❯

in implementation of those if requested . Innovation and AI Enablement: Evaluate and support implementation of innovative technologies, including agentic AI, to enhance contract review, negotiation, risk flagging, and metadata extraction. Lead the functional design and implementation of intelligent contract features, ensuring they are fit-for-purpose and deliver business value. Change Management: Lead change management for CLM-related initiatives. More ❯

at midnight Are you passionate about data and making a difference in the public sector? The National Archives is looking for a talented data specialist to transform archival metadata bringing history to life. About Us: At The National Archives, multidisciplinary and interdisciplinary research into all aspects of our collections and activities is at the heart of what we do. This More ❯

and best practices Collaborating with engineers, architects, and stakeholders to align data models with business needs Leading on data integration, transformation, and migration strategies Owning enterprise data models, dictionaries, metadata, and lineage Optimising for performance, scalability, and compliance What we’re looking for: 10+ years in data architecture and modelling Deep experience with 3NF, dimensional, and Vault 2.0 modelling Real More ❯

and best practices Collaborating with engineers, architects, and stakeholders to align data models with business needs Leading on data integration, transformation, and migration strategies Owning enterprise data models, dictionaries, metadata, and lineage Optimising for performance, scalability, and compliance What we’re looking for: 10+ years in data architecture and modelling Deep experience with 3NF, dimensional, and Vault 2.0 modelling Real More ❯

Architecture, and its roadmap; youll provide advisory and governance support to ensure projects align to simplification strategy and comply with data standards while promoting and supporting effective data modelling, metadata management and alignment to enterprise data model and data controls. Well look to you to influence the development of business strategies at an organisational level, identifying transformational opportunities for our More ❯

into a unified data platform. Cleanse, transform, and model data to support BI tools (e.g., Power BI) and AI/ML use cases. Implement data validation, lineage tracking, and metadata tagging for observability and trust. Collaborate with stakeholders to standardise KPIs and support cross-functional reporting. Ensure secure handling of sensitive data in line with GDPR and internal policies. What More ❯

into a unified data platform. Cleanse, transform, and model data to support BI tools (e.g., Power BI) and AI/ML use cases. Implement data validation, lineage tracking, and metadata tagging for observability and trust. Collaborate with stakeholders to standardise KPIs and support cross-functional reporting. Ensure secure handling of sensitive data in line with GDPR and internal policies. What More ❯

into a unified data platform. Cleanse, transform, and model data to support BI tools (e.g., Power BI) and AI/ML use cases. Implement data validation, lineage tracking, and metadata tagging for observability and trust. Collaborate with stakeholders to standardise KPIs and support cross-functional reporting. Ensure secure handling of sensitive data in line with GDPR and internal policies. What More ❯

into a unified data platform. Cleanse, transform, and model data to support BI tools (e.g., Power BI) and AI/ML use cases. Implement data validation, lineage tracking, and metadata tagging for observability and trust. Collaborate with stakeholders to standardise KPIs and support cross-functional reporting. Ensure secure handling of sensitive data in line with GDPR and internal policies. What More ❯

into a unified data platform. Cleanse, transform, and model data to support BI tools (e.g., Power BI) and AI/ML use cases. Implement data validation, lineage tracking, and metadata tagging for observability and trust. Collaborate with stakeholders to standardise KPIs and support cross-functional reporting. Ensure secure handling of sensitive data in line with GDPR and internal policies. What More ❯

into a unified data platform. Cleanse, transform, and model data to support BI tools (e.g., Power BI) and AI/ML use cases. Implement data validation, lineage tracking, and metadata tagging for observability and trust. Collaborate with stakeholders to standardise KPIs and support cross-functional reporting. Ensure secure handling of sensitive data in line with GDPR and internal policies. What More ❯

consistent communication with teams to report progress, risks, and issues. Knowledge, Skills, Experience & Qualifications: Essential: Strong knowledge of Transactional Data types and Bank Products. Expertise in data governance, quality, metadata, profiling, analysis, and management tools. Problem-solving aptitude with effective communication skills. Understanding of enterprise-wide data governance practises. Confident stakeholder engagement abilities. Proficient in Microsoft Office Suite (Word, Excel More ❯

consistent communication with teams to report progress, risks, and issues. Knowledge, Skills, Experience & Qualifications: Essential: Strong knowledge of Transactional Data types and Bank Products. Expertise in data governance, quality, metadata, profiling, analysis, and management tools. Problem-solving aptitude with effective communication skills. Understanding of enterprise-wide data governance practises. Confident stakeholder engagement abilities. Proficient in Microsoft Office Suite (Word, Excel More ❯

Governance Engineer to join our Security Team. What You Will Be Doing: Implement Technical Controls: Build and maintain a centralized data inventory, business glossary, and data mapping framework using metadata management and data catalog tools. Automate data classification, lineage tracking, and policy enforcement through scripts, APIs, and orchestration tools (e.g., dbt, Airflow). Map & Visualize Data Flows : Design and maintain More ❯

AI/ML priorities. Collaborate with business and technical stakeholders to align data capabilities with innovation goals. Data Governance & Quality Build and lead robust data governance frameworks, policies, and metadata practices. Drive enterprise data quality standards including accuracy, completeness, and timeliness. Ensure regulatory compliance and enable AI transparency through data lineage and oversight. Market Data Management Own the strategy and More ❯

Collaborate on AI platform designs leveraging Dell's product and partner ecosystem e.g. NVAIE, Run.ai, H2O.ai, ClearML, OpenShift, etc. Provide expert guidance on modern data stack components: data quality, metadata management, observability, data products, feature stores, with governance and Dell's maturity model frameworks. Stay current on emerging AI and associated Data Management technologies. Actively contribute field feedback to Dell More ❯

leading across Product, Engineering, and Data teams. Experience navigating ambiguity and delivering structure to complex, evolving domains. We'd love to see: Experience with data governance, quality frameworks, and metadata management. Understanding of third-party entity data providers and integration strategies. Experience with modern data infrastructure and architecture, including APIs, data pipelines, or LLM-based enrichment solutions. Awareness of emerging More ❯

leading across Product, Engineering, and Data teams. Experience navigating ambiguity and delivering structure to complex, evolving domains. We'd love to see: Experience with data governance, quality frameworks, and metadata management. Understanding of third-party entity data providers and integration strategies. Experience with modern data infrastructure and architecture, including APIs, data pipelines, or LLM-based enrichment solutions. Awareness of emerging More ❯