with other data sets, enabling reuse. You can work with other data professionals to improve modelling and integration patterns and standards. (Skill level: Practitioner) Metadata Management: You can design an appropriate metadatarepository and suggest changes to improve current metadata repositories. You can understand a range … of tools for storing and working with metadata, advising others about metadata management. (Skill level: Practitioner) Problem Management: You can initiate and monitor actions to investigate patterns and trends to resolve patterns, effectively consulting specialists as required. You can determine the appropriate resolution and assist with its implementation More ❯
applications and organisations Understand industry-recognised data modelling patterns and standards, and when to apply them. Compare and align different data models. Designing appropriate metadata repositories and present changes to existing metadata repositories Understand a range of tools for storing and working with metadata Designing data architecture More ❯
role requires strong communication skills to collaborate effectively with both technical and non-technical stakeholders. You will be responsible for data governance, data modelling, metadata management, and ensuring compliance with data standards. Key Responsibilities: 1. Data Architecture & Engineering Design and implement scalable data architectures that align with business objectives. … Governance & Compliance Ensure adherence to data governance policies and regulatory requirements. Monitor and maintain compliance with data standards and security measures. Develop and manage metadata repositories for accurate data tracking and integration. Support data assurance processes and provide recommendations for compliance improvements. 3. Data Analysis & Communication Conduct data profiling … Strong proficiency in Java, SQL, Python, SparkSQL, and PySpark. Experience with Microsoft Power Platform (PowerApps, Power Automate, etc.). Good understanding of data governance, metadata management, and compliance frameworks. Ability to communicate effectively with both technical and non-technical stakeholders. Experience in data modelling, data profiling, and source system More ❯
modelling tools Data Standards: Developed data standards in support of data interoperability; written technical specifications; assured code/systems against standards; championed data standards Metadata Management: Designed/Developed data catalogues or metadata repositories; used tools like Apache Atlas/Hive Metastore/AWS Glue/AWS Datazone More ❯
