1 to 25 of 255 Metadata Jobs in England

managing large-scale data solutions on Microsoft Azure. Unity Catalog Mastery: In-depth knowledge of setting up, configuring, and utilizing Unity Catalog for robust data governance, access control, and metadata management in a Databricks environment. Databricks Proficiency: Demonstrated ability to optimize and tune Databricks notebooks and workflows to maximize performance and efficiency. Experience with performance troubleshooting and best practices for More ❯

Design and build robust data pipelines with Cloud Composer, Dataproc, Dataflow, Informatica, or IBM DataStage, supporting both batch and streaming data ingestion. Data Governance & Quality: Implement data governance frameworks, metadata management, and data quality controls using Unity Catalog, Profisee, Alation, DQ Pro, or similar platforms. Client Engagement & Advisory: Act as a trusted advisor to clients senior leadership (CDOs, CIOs, Heads 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 ❯

on strategic, cross-functional data initiatives with C-level stakeholders. Familiarity with cloud data platforms (e.g., Azure, AWS, GCP, Snowflake). Knowledge of data governance standards, regulatory compliance, and metadata management. Experience with BI and visualization tools such as Power BI, Tableau, or Looker. Certification in data science, analytics, or cloud technologies (e.g., Microsoft, AWS, Google). Why join Genpact More ❯

on strategic, cross-functional data initiatives with C-level stakeholders. Familiarity with cloud data platforms (e.g., Azure, AWS, GCP, Snowflake). Knowledge of data governance standards, regulatory compliance, and metadata management. Experience with BI and visualization tools such as Power BI, Tableau, or Looker. Certification in data science, analytics, or cloud technologies (e.g., Microsoft, AWS, Google). Why join Genpact More ❯

APIs, and machine learning models in coordination with DevOps teams. Define and embed best practices for data warehousing and Lakehouse architecture (e.g. Medallion). Standardise data development, modelling, and metadata management across the enterprise. Implement lineage tracking and orchestration tools to improve transparency and governance. Conduct code reviews, testing, and documentation to ensure quality and robustness of analytics outputs. Take More ❯

Governance and Quality Assurance: Embed governance, security, and data quality practices into engineering workflows. Define guardrails and reference implementations for data access control, data lineage, and compliance. Promote consistent metadata management and enforce technical standards to ensure trust in data assets. Stakeholder Engagement: Collaborate with PN D&A leadership, PN product owners, and segment D&A leadership to synchronize and More ❯

Governance and Quality Assurance: Embed governance, security, and data quality practices into engineering workflows. Define guardrails and reference implementations for data access control, data lineage, and compliance. Promote consistent metadata management and enforce technical standards to ensure trust in data assets. Stakeholder Engagement: Collaborate with PN D&A leadership, PN product owners, and segment D&A leadership to synchronize and 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. In accordance with the Employment Agencies and Employment Businesses Regulations More ❯

data from SAP (e.g., S/4HANA, BW/4HANA) and non-SAP sources (e.g., cloud platforms, APIs, third-party systems). Establish and enforce data governance policies including metadata management, data lineage tracking, and access control to ensure data integrity and compliance. Optimize data pipelines and transformation logic using SAP Datasphere's capabilities to support real-time and batch More ❯

Governance and Quality Assurance: Embed governance, security, and data quality practices into engineering workflows. Define guardrails and reference implementations for data access control, data lineage, and compliance. Promote consistent metadata management and enforce technical standards to ensure trust in data assets. Stakeholder Engagement: Collaborate with PN D&A leadership, PN product owners, and segment D&A leadership to synchronize and More ❯

Governance and Quality Assurance: Embed governance, security, and data quality practices into engineering workflows. Define guardrails and reference implementations for data access control, data lineage, and compliance. Promote consistent metadata management and enforce technical standards to ensure trust in data assets. Stakeholder Engagement: Collaborate with PN D&A leadership, PN product owners, and segment D&A leadership to synchronize and More ❯

meetings 2. Data Governance & Quality: Establish and enforce data governance policies, standards, and procedures Define data quality rules and implement processes for data validation and cleansing Design and implement metadata management strategies Architect secure data storage, access controls, and data privacy measures Develop and implement Master Data Management (MDM) strategies Partner closely with the Enterprise Architect, Integration Architect, business stakeholders More ❯

governance, security, and compliance strategies. Lead the integration of core data management capabilities , including: Master Data Management (MDM) solutions for single-source-of-truth data Data catalogue tools for metadata management and discovery Data governance frameworks for policy enforcement, compliance, and lineage tracking Data quality solutions to ensure data accuracy, consistency, and reliability Provide architectural leadership on hub-and-spoke More ❯

into technical specifications and ensure timely delivery of data products. 4. Data Quality & Governance Implement monitoring systems to ensure data accuracy, completeness, and timeliness. Support data governance initiatives, including metadata management, lineage tracking, and access controls. Ensure compliance with regulatory standards (e.g., REMIT, EMIR) and internal audit requirements. 5. Innovation & Continuous Improvement Evaluate and adopt new technologies (e.g., streaming platforms More ❯

capability for working with unstructured and semi-structured datasets, transforming raw information into actionable insights. Data Workflow Development: Expertise in developing and maintaining data transformation processes, managing data structures, metadata, workload dependencies, and orchestration frameworks. Large-scale Data Processing: A demonstrated history of manipulating, processing, and extracting value from large, diverse, and disconnected datasets in fast-moving environments. Project Management More ❯

capability for working with unstructured and semi-structured datasets, transforming raw information into actionable insights. Data Workflow Development: Expertise in developing and maintaining data transformation processes, managing data structures, metadata, workload dependencies, and orchestration frameworks. Large-scale Data Processing: A demonstrated history of manipulating, processing, and extracting value from large, diverse, and disconnected datasets in fast-moving environments. Project Management More ❯

Capability for working with unstructured and semi-structured datasets, transforming raw information into actionable insights. Data Workflow Development: Skilled in developing and maintaining data transformation processes, managing data structures, metadata, workload dependencies, and orchestration frameworks. Large-scale Data Processing: A demonstrated history of manipulating, processing, and extracting value from large, diverse, and disconnected datasets in fast-moving environments. Project Management More ❯

Capability for working with unstructured and semi-structured datasets, transforming raw information into actionable insights. Data Workflow Development: Skilled in developing and maintaining data transformation processes, managing data structures, metadata, workload dependencies, and orchestration frameworks. Large-scale Data Processing: A demonstrated history of manipulating, processing, and extracting value from large, diverse, and disconnected datasets in fast-moving environments. Project Management More ❯

and analytics. Data Modelling & Design: Design and implement logical and physical data models that support the analytical and modelling requirements of the platform. Define data dictionaries, data lineage, and metadata management processes. Ensure data consistency, integrity, and quality across the platform. Data Integration & Pipelines: Define data integration patterns and establish robust data pipelines for ingesting, transforming, and loading data from … financial markets is highly desirable. Excellent communication, interpersonal, and presentation skills. Strong analytical and problem-solving skills. Experience with data visualisation tools (e.g., Tableau, Power BI). Experience with metadata management tools e.g. Purview. Knowledge of data science and machine learning concepts. Experience with API design and development. #J-18808-Ljbffr More ❯

discovery, evaluating source systems and APIs, and creating stories for implementation Collaborate with third parties to ensure interoperability and integration compatibility Champion best practices in warehousing techniques (e.g. Kimball), metadata management, and performance optimisation Support delivery through integration testing, reconciliation, and reporting visualisation (e.g. Power BI, Tableau) About You: Proven experience designing data architectures for large-scale platforms and diverse More ❯

discovery, evaluating source systems and APIs, and creating stories for implementation Collaborate with third parties to ensure interoperability and integration compatibility Champion best practices in warehousing techniques (e.g. Kimball), metadata management, and performance optimisation Support delivery through integration testing, reconciliation, and reporting visualisation (e.g. Power BI, Tableau) About You: Proven experience designing data architectures for large-scale platforms and diverse More ❯

discovery, evaluating source systems and APIs, and creating stories for implementation Collaborate with third parties to ensure interoperability and integration compatibility Champion best practices in warehousing techniques (e.g. Kimball), metadata management, and performance optimisation Support delivery through integration testing, reconciliation, and reporting visualisation (e.g. Power BI, Tableau) About You: Proven experience designing data architectures for large-scale platforms and diverse More ❯

discovery, evaluating source systems and APIs, and creating stories for implementation Collaborate with third parties to ensure interoperability and integration compatibility Champion best practices in warehousing techniques (e.g. Kimball), metadata management, and performance optimisation Support delivery through integration testing, reconciliation, and reporting visualisation (e.g. Power BI, Tableau) About You: Proven experience designing data architectures for large-scale platforms and diverse More ❯

discovery, evaluating source systems and APIs, and creating stories for implementation Collaborate with third parties to ensure interoperability and integration compatibility Champion best practices in warehousing techniques (e.g. Kimball), metadata management, and performance optimisation Support delivery through integration testing, reconciliation, and reporting visualisation (e.g. Power BI, Tableau) About You: Proven experience designing data architectures for large-scale platforms and diverse More ❯