Edinburgh, Midlothian, United Kingdom Hybrid / WFH Options
Aberdeen Group
DAMA-DMBOK to guide enterprise data strategy and governance. Design and implement data integration pipelines using ETL/ELT methodologies and API-driven architectures. Oversee data governance initiatives including metadata management, data quality, and master data management (MDM). Evaluate and integrate big data technologies and streaming platforms such as Apache Kafka and Apache Spark. Collaborate with cross-functional teams More ❯
Edinburgh, Midlothian, United Kingdom Hybrid / WFH Options
Aberdeen
to support analytics, regulatory reporting, and operational use cases. Promote and implement engineering best practices, including test automation, unit testing, and CI/CD pipelines. Support data governance and metadata management initiatives to ensure data integrity and compliance. Explore and apply AI-assisted development tools (eg GitHub Copilot) and automation to improve engineering efficiency and solution quality. About the Candidate More ❯
proficiency in data modelling (conceptual, logical, physical) across relational, dimensional, and NoSQL paradigms. Skilled in data integration, ETL/ELT design, and API-driven architectures. Experience with data governance, metadata management, and master data management They're big on expertise, not hierarchy, so you'll be trusted with more responsibility while supported by everyone around you. You'll be encouraged More ❯
our clients in the Data Management and Governance team. Our end-to-end experience allows our Data practitioners to advise on Data management and Strategy, Modelling, MDM, Data Quality, Metadata Management, Data Privacy and compliance through to Data Mesh and Marketplace. Our technology and consulting expertise and breadth skills enables transformational change at any scale. As a Data Management Associate … and dashboards to monitor and report on data health Lead end-to-end delivery of data quality initiatives, from requirements gathering to deployment and support Integrate DQ solutions with metadata repositories and data governance platforms Provide technical guidance and best practices for data profiling, cleansing, and validation Explore and apply AI-driven techniques (e.g., GenAI) to enhance data quality automation More ❯
