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 3. Collaboration & Mentorship: Partner closely with the Enterprise Architect, Integration 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 ❯
Data Strategy Define and lead enterprise-wide data strategy Design and maintain a scalable, secure data architecture Deep understanding of Data Governance Modern data platforms: Cloud Data Quality Management, metadata, lineage, and data modelling Experience with Data integration, master data management (MDM), and designing scalable data pipelines Data Privacy, regulatory compliance, and security best practices BI Tools: Power BI, Tableau More ❯
Data Strategy Define and lead enterprise wide data strategy Design and maintain a scalable, secure data architecture Deep understanding of Data Governance, Modern data platforms: Cloud Data quality Management, metadata, lineage and data modelling Experience with Data integration, master data management (MDM) and designing scalable data pipelines Data Privacy, regulatory compliance, and security best practises BI Tools Power BI, Tableau More ❯
Data Strategy Define and lead enterprise wide data strategy Design and maintain a scalable, secure data architecture Deep understanding of Data Governance, Modern data platforms: Cloud Data quality Management, metadata, lineage and data modelling Experience with Data integration, master data management (MDM) and designing scalable data pipelines Data Privacy, regulatory compliance, and security best practises BI Tools Power BI, Tableau More ❯
Data Strategy Define and lead enterprise wide data strategy Design and maintain a scalable, secure data architecture Deep understanding of Data Governance, Modern data platforms: Cloud Data quality Management, metadata, lineage and data modelling Experience with Data integration, master data management (MDM) and designing scalable data pipelines Data Privacy, regulatory compliance, and security best practises BI Tools Power BI, Tableau More ❯
London, South East, England, United Kingdom Hybrid / WFH Options
Precise Placements
transactional, analytical, and operational systems Architect solutions for data lakes, warehouses, and master data management (MDM) Establish reference architecture for data ingestion, transformation, storage, and consumption Champion data quality, metadata, and governance standards (including GDPR compliance) Provide architectural oversight on multi-cloud and hybrid environments Collaborate with stakeholders to enable data-driven decision-making and new revenue streams Skills & Experience More ❯
engagement, and ensure alignment across business, IT, compliance, and security teams. Establish data quality metrics, rules, and monitoring mechanisms across cloud data pipelines and lakehouses. Champion the use of metadata management, data catalogs (e.g., Azure Purview, Unity Catalog), and standardized business glossaries. Provide governance oversight for data sharing and consumption in Databricks notebooks, Power BI reports, and machine learning workflows. 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 ❯
principles of data modelling Re-engineer data pipelines to be scalable, robust, automatable, and repeatable Navigate, explore and query large scale datasets Build processes supporting data transformation, data structures, metadata, dependency and workload management Identify and resolve data issues including data quality, data mapping, database and application issues Implement data flows to connect operational systems, data for analytics and business More ❯
Plainsboro, New Jersey, United States Hybrid / WFH Options
Genmab
in biotech/pharma data platforms. Experience designing and implementing data mesh architectures and data marketplaces. Proven ability to work with data governance teams to ensure alignment with enterprise metadata management, lineage tracking, and access control. Excellent stakeholder management, communication, and influencing skills across technical and non-technical teams. Biotech or pharma experience is required, with a deep understanding of More ❯
principles of data modelling • Re-engineer data pipelines to be scalable, robust, automatable, and repeatable • Navigate, explore and query large scale datasets • Build processes supporting data transformation, data structures, metadata, dependency and workload management • Identify and resolve data issues including data quality, data mapping, database and application issues • Implement data flows to connect operational systems, data for analytics and business More ❯
policies, underwriting Effective stakeholder communication and delivery focus Strong project and time management in fast-paced environments Desirable Tools and Tech Power BI, Tableau, Looker, Domo Data governance and metadata management tools DevOps for data workflows, hybrid/multi-cloud architectures Monitoring and cost optimisation tools (Azure Monitor, GCP cost tools) Culture and Conduct Act as a role model for More ❯
London, South East, England, United Kingdom Hybrid / WFH Options
Become
of BCBS239, risk and finance data structures, and data governance best practices Proven experience influencing and engaging senior stakeholders across complex organisations Strong working knowledge of data quality, profiling, metadata management, and governance tools (Collibra preferred) Analytical mindset with the ability to challenge constructively and solve problems creatively Experience working in Tier 1/Tier 2 banking, with a solid More ❯
and efficiency. Design and govern data architecture and integration standards across Azure Data Factory and Databricks to enable integrated analytics solutions. Support Munich Re's pillars for Data Governance, Metadata Management, MDM, Data Quality, Data Warehousing, Sourcing and Staging of data, BI, Advanced Analytics, and R&D, in close alignment with business functions and enterprise information management. Manage the Information More ❯
principles of data modelling Re-engineer data pipelines to be scalable, robust, automatable, and repeatable Navigate, explore and query large scale datasets Build processes supporting data transformation, data structures, metadata, dependency and workload management Identify and resolve data issues including data quality, data mapping, database and application issues Implement data flows to connect operational systems, data for analytics and business More ❯
data from SAP (e.g., S/4HANA, BWS/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 SAC's capabilities to support real-time and batch More ❯
data from SAP (e.g., S/4HANA, BWS/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 ❯
implementing cloud data migration and storage patterns on one or more of AWS, GCP and Microsoft Azure Experience implementing and integrating data management platforms for data cataloguing, classification and metadata management. Experience designing and developing data privacy, security and entitlements frameworks for cloud provider ecosystems (AWS, Azure, GCP). Good understanding of cloud networking architecture, operations, automation and cost management. More ❯
conceptual, logical and physical data models to provide structured view of data domains, entities, and their relationships. Data Documentation: Create and update data dictionaries, entity-relationship diagrams (ERDs), and metadata to ensure clarity and consistency. Stakeholder Collaboration: Collaborate closely with business stakeholders to understand data requirements and translate them into structured data models that meet business needs. Data Governance Alignment More ❯
conceptual, logical and physical data models to provide structured view of data domains, entities, and their relationships. Data Documentation: Create and update data dictionaries, entity-relationship diagrams (ERDs), and metadata to ensure clarity and consistency. Stakeholder Collaboration: Collaborate closely with business stakeholders to understand data requirements and translate them into structured data models that meet business needs. Data Governance Alignment More ❯
Manchester, Lancashire, United Kingdom Hybrid / WFH Options
Capgemini
conceptual, logical and physical data models to provide structured view of data domains, entities, and their relationships. Data Documentation: Create and update data dictionaries, entity-relationship diagrams (ERDs), and metadata to ensure clarity and consistency. Stakeholder Collaboration: Collaborate closely with business stakeholders to understand data requirements and translate them into structured data models that meet business needs. Data Governance Alignment More ❯
consistent data standards across the enterprise. Provide technical support and customer service to both headquarters and field users. Oversee the PSP system's content, auditing for missing or inappropriate metadata, and escalate technical issues as necessary. Ensure the efficient scheduling, processing, and documentation of data delivery and implementation, leveraging automation when feasible. Required Qualifications: Active Top Secret security clearance Bachelor More ❯
opportunity is for you. RESPONSIBILITIES Work with teams of data and system engineers to design, develop, build, analyze, and evaluate data management systems, including database modeling, relational database architecture, metadata, and configuration management. Use data mapping, data mining, and data transformation tools to design and develop integrated data repositories. Integrate disparate raw data across a federated enterprise using Extract, Transform More ❯