Data Architect - Data Platform - Data Modeling - MDM - Data Management - Azure

As a Senior Data Architect, you will align the organisation’s data architecture with its overall data strategy, establishing robust standards, governance and data models that enable business value while managing risk.

Working closely with the Data, Technology and business teams, you will lead data architecture across business-critical initiatives, define semantic data layers, improve data quality and ensure consistent, compliant and efficient use of data.

What You’ll Be Doing:

• Develop and maintain data architecture policies, standards, models and governance in collaboration with InfoSec, Technology, GCT and Information & Records.
• Own and manage logical and physical data models, including metadata, business glossaries, data flows and storage.
• Lead architectural assurance for major projects and changes, assessing designs against standards, identifying impacts and recommending appropriate mitigations.
• Provide expert guidance on data modelling, integration, master data, metadata, migration and analytics.
• Ensure project data deliverables align with the organisation’s data architecture and strategic objectives.
• Champion data architecture and governance through thought leadership, mentoring and knowledge sharing.
• Identify opportunities to improve data capabilities, deliver business value and optimise the use of data.
• Assess the impact of emerging technologies and industry trends on data architecture and strategy.

• Proven experience developing and implementing data architecture artefacts, policies, standards and governance frameworks.
• Strong knowledge of data management, data governance, data quality, MDM, metadata, data migration, integration, BI/analytics, security and privacy.
• Strong understanding of business data domains, processes and regulatory/compliance requirements, ideally within a professional services or legal environment.
• Extensive experience with conceptual, logical and physical data modelling, including transactional, analytical and relational models.
• Experience working with data models across multiple technologies, including RDBMS and APIs.
• Strong experience producing ERDs, data models, star schemas, data dictionaries, taxonomies and ontologies.
• Experience managing metadata repositories and using metadata to support data lineage, integration and impact analysis.