151 to 175 of 635 Permanent Metadata Jobs

ownership and stewardship models, target operating models, data architectures and implementation roadmaps. Strong understanding of master data management, data quality, data migration, data integration, metadata, reporting and analytics, with the ability to connect these disciplines into a coherent client solution. Experience leading large, distributed and multidisciplinary delivery teams, including onshore ...

adopting strategic tooling and assets. What you’ll bring Essential criteria: Demonstrated expertise across data management and data governance, including data ownership, data quality, metadata management, data lineage and data cataloguing. Proficiency with data management and data governance technologies and tooling. Experience supporting the design and implementation of Data & Information ...

through discovery, design, build, validation and release, while maintaining clear separation between product outcomes and delivery execution. · Data Governance, Quality & Controls: Define ownership, lineage, metadata, access controls, reconciliation and quality expectations so that premium data is trusted, auditable and suitable for authorised use. · Adoption & Value Realisation: Define success measures, monitor ...

Board level Data Deep expertise in data management disciplines, including: Data governance and stewardship models Data management and controls Master and reference data management Metadata management and data lineage Experience establishing and scaling a data governance function (policies, frameworks, controls, ownership models) Strong understanding of data architecture principles, including modern ...

capabilities supporting multiple of technology assets. Establish engineering standards, design patterns, and platform guardrails for telemetry collection and observability data management. Drive adoption of metadata‐driven routing, schema normalization, data classification, and governance across enterprise logging ecosystems. Build highly resilient, scalable, and cost‐efficient telemetry pipelines capable of handling large ...

domain including but not limited to: Data Strategy, Business Intelligence and Analytics, Data Management, Data Modelling, Data Quality, Data Governance, Master Data Management and Metadata Management. Ability to build relationships and influence C suite stakeholders in a Strategy Consulting context Subject Matter expertise in AI with a deep understanding ...

ownership and stewardship models, target operating models, data architectures and implementation roadmaps. Strong understanding of master data management, data quality, data migration, data integration, metadata, reporting and analytics, with the ability to connect these disciplines into a coherent client solution. Experience leading large, distributed and multidisciplinary delivery teams, including onshore ...

limited to, the following: Gather business requirements, analyze source systems, define underlying data sources and transformation requirements, design data models, and develop metadata for data analysis and visualization Acquire and analyze data and metrics across the enterprise to learn how they can be incorporated into data visualizations and dashboards Collaborate ...

domain including but not limited to: Data Strategy, Business Intelligence and Analytics, Data Management, Data Modelling, Data Quality, Data Governance, Master Data Management and Metadata Management.Ability to build relationships and influence C suite stakeholders in a Strategy Consulting contextSubject Matter expertise in AI with a deep understanding of its usage ...

Studio and agents, Azure AI/OpenAI, machine learning) A clear understanding of what makes a data estate AI-ready – content quality and structure, metadata, unstructured data preparation, permissions and oversharing risk – and the ability to shape propositions around it Working knowledge of the UK data and AI regulatory landscape ...

Studio and agents, Azure AI/OpenAI, machine learning) A clear understanding of what makes a data estate AI-ready – content quality and structure, metadata, unstructured data preparation, permissions and oversharing risk – and the ability to shape propositions around it Working knowledge of the UK data and AI regulatory landscape ...

Studio and agents, Azure AI/OpenAI, machine learning) A clear understanding of what makes a data estate AI-ready – content quality and structure, metadata, unstructured data preparation, permissions and oversharing risk – and the ability to shape propositions around it Working knowledge of the UK data and AI regulatory landscape ...

practices around security, scalability, performance and cost optimisation . Provide technical leadership, architecture governance and design documentation across data initiatives. Develop data quality, governance, metadata and data management frameworks. Explore how AI and Machine Learning can enhance data solutions through automation, anomaly detection and predictive data quality. Translate complex technical … Microsoft Fabric, Databricks or equivalent. Strong understanding of data modelling, data warehousing, Lakehouse and modern data architecture. Experience with data governance, data quality and metadata management. Exposure to AI/ML integration within data solutions and an understanding of AI governance. Experience with visualisation platforms such as Power BI, Tableau ...

physical data models design Fact, Dimension and Bridge tables, including conformed dimensions and surrogate keys develop data warehouse and data mart models develop metadata management structures and data dictionaries translate business and technical requirements into structured data models and specifications collaborate with multiple squads to embed consistent modelling standards ...

lakes (e.g., Snowflake, Redshift, Teradata, BigQuery). Strong analytical, problem-solving, and communication skills. Knowledge of BI lifecycle and governance, including report certification and metadata usage. Familiarity with ETL tools and scripting (Python/Alteryx/SSIS) is a plus. Ability to work in Agile/DevOps environments, collaborating with ...

developing AI-led engineering teams. Core skills: Modern Data Architecture: Data Mesh Data Products Enterprise Data Models Logical and Physical Data Modelling Data Warehousing Metadata-driven architectures Data Fabric concepts Event-driven architectures Enterprise ingestion and transformation patterns Data interoperability and consumption readiness design principles. Cloud Data Engineering: Google Cloud ...

Perform end-to-end testing of SAP Datasphere components including: Spaces, Connections, Data Flows, Views, and Analytical Models. Semantic modelling, business layer definitions, and metadata structures. Validate data pipelines, transformations, lineage, and modelling consistency across environments. Ensure alignment of Datasphere models with enterprise architecture and reporting needs. HR Domain Testing ...

translating control requirements to required activities. Preferred qualification, skills and capabilities Knowledge of data management capabilities, such as lifecycle management, data quality (DQ) management, metadata management, data classification, data lineage, data privacy or data integration. Knowledge of data management technologies (e.g. data retention, data integration, data visualization, analytics) and integration ...

technologies, tools and data solutions across the business Defining architectural standards, best practices and reusable patterns across engineering teams Supporting data governance, security, metadata and data quality initiatives Providing hands-on guidance around Terraform, dbt, CI/CD, DataOps and platform engineering practices Partnering with stakeholders to understand requirements ...

data governance, data science, data engineering, data quality, and data security best practices. Proven ability to independently tackle design and functionality challenges. Experience managing metadata and data management constructs, including business glossaries and technical data dictionaries. Familiarity with GDPR and other data protection and privacy regulations applicable ...

Experience leading cross-functional teams including Data Engineers, Data Architects, Business Analysts, Reporting teams, and Business stakeholders. Strong knowledge of data governance, data quality, metadata management, data lineage, and regulatory/compliance requirements. Proven ability to manage end-to-end delivery of data transformation initiatives, including roadmap planning, risk management ...

discover, classify and tag sensitive data across Snowflake and other sources, and tune classifiers to reduce false positives Connect BigID classifications and Collibra metadata to Immuta to drive automated, tag‐based access policies Translate privacy, regulatory and internal data handling requirements, including GDPR, into enforceable technical controls Define and implement ...

cross-functional teams, ensuring best practices in data architecture, security, and cloud computing Proficiency in data modelling, ETL processes, data warehousing, distributed systems and metadata systems Utilise Apache Flink and other streaming technologies to build real-time data processing systems that handle large-scale, high-throughput data Ensure all data ...

leading multidisciplinary technical and analytical teams. Experience developing data products, semantic models, executive dashboards and measurement frameworks. Strong knowledge of data governance, quality, lineage, metadata, reporting controls and evidence. Experience translating complex technology information into concise, decision‐oriented executive insight. Knowledge of predictive analytics, forecasting, automation and the responsible ...

with business owners to translate business requirements into technical specifications and solution designs that satisfies the data requirements of the business. Experience working with metadata management products such as Cloud Data Catalog and Collibra and Data Governance tools like Dataplex Experience in developing solutions on GCP using cloud‐native principles ...