Data Architect

About the role

Guardrisk is seeking an experienced Data Architect to design and govern enterprise‑grade Azure data platforms. The role focuses on delivering secure, scalable, and high‑performance solutions that meet business and regulatory requirements, reporting to the Enterprise Solutions Architect.

Key responsibilities

• Design and implement Azure‑based data solutions including Azure SQL, Synapse, Cosmos DB, Data Lake, Databricks and Dataverse.
• Ensure platform performance, resilience, cost optimisation and security.
• Develop conceptual, logical and physical data models aligned to business domains.
• Lead migration of legacy systems to cloud‑native architectures, overseeing schema conversion, data mapping and validation.
• Define and enforce data lifecycle management standards and ensure compliance with POPIA, GDPR and internal governance.
• Deliver integrated analytics using Power BI, Azure Analysis Services and Azure Machine Learning.
• Provide architectural guidance for data‑driven applications and integration with Microsoft 365, Power Platform and Dynamics 365.
• Implement CI/CD pipelines, Infrastructure‑as‑Code (Terraform) and automated data pipelines (ADF, Power Automate).
• Establish data quality frameworks and monitoring using Azure Monitor, Purview and related tools.
• Mentor junior architects and participate in governance forums.

Required profile

• Relevant 3–4 year IT or Business qualification (BCom, BSc or equivalent).
• 7+ years of enterprise data architecture experience, including large‑scale cloud and hybrid platforms.
• 5+ years of experience in the insurance industry.
• Proven ability to deliver end‑to‑end data platforms and lead modernization initiatives.

Required skills

• Azure SQL, Azure Synapse, Azure Cosmos DB, Azure Data Lake, Azure Databricks, Azure Dataverse.
• Power BI, Azure Analysis Services, Azure Machine Learning.
• Azure Data Factory, Azure Monitor, Azure Purview.
• Terraform, CI/CD, Infrastructure‑as‑Code.
• Data modelling (dimensional, star/snowflake schemas, semantic layers).
• Data governance, MDM, data quality and observability frameworks.
• Compliance knowledge of POPIA and GDPR.