Synapri
Senior Data Architect
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Senior 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. 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. The role has a focus on the Building of their Data Platform, Data Modeling, and Master Data Management.
What You'll Be Doing:
- Develop and maintain data architecture policies, standards, models, and governance.
- 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.
- Identify opportunities to improve data capabilities, deliver business value, and optimise the use of data.
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About You:
- 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.
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