Data architect (insurance)

This role will lead the design and implementation of cloud-native data architectures using medallion and modern data lake architectures, integrating services such as Azure SQL, Synapse, Cosmos DB, Data Lake, Databricks, Py Spark Notebooks, Power BI, and Dataverse. The Role will also drive innovation in data analytics, automation, and application development, while fostering collaboration across IT, business, and governance teams.

Essentials requirements for this position: Non negotiables: Data Modelling, Databricks, Data Quality, and Large Volume / Multi Data Lake Structures. Financial Services experience at least it’s not only insurance The following is required to be considered for this position: BCom or BSc degree or equivalent in IT | Business qualification Minimum 7 years of experience in enterprise-level data architecture, solution design and modeling of insurance-based data technologies Proven ability to lead large-scale data platform implementations across hybrid and cloud environments Expertise in designing scalable, secure and cost-effective data architectures in the cloud aligned with business and regulatory requirements Extensive hands‑on experience with: Azure SQL Database, Azure Synapse Analytics, Azure Cosmos DB Azure Blob Storage, Azure Data Lake Storage Azure Data Factory, Azure Stream Analytics Azure Analysis Services, Azure Machine Learning Strong understanding of Azure-native data integration, transformation and analytical capabilities Data Modeling and Semantic Layer Design: Proficient in conceptual, logical and physical data modeling using tools like Visio, Azure Synapse, Power BI and Databricks Experience designing semantic models for Power BI and Azure Analysis Services to support enterprise-wise reporting Skilled in dimensional modeling, star/snowflake schemas and metadata management Data Quality and Observability: Implemented data quality frameworks and observability practices using Azure Monitor, Purview and custom telemetry tools working closely with the Data Architect Experience with anomaly detection, data validation rules and lineage tracking to ensure trust and transparency Defined and monitored data SLA’s and KPI’s across business-critical pipelines Master Data Management (MDM): Experience implementing and integrating Master Data Management solutions to ensure consistency of key business entities across systems Defined governance models and stewardship processes for managing golden records, resolving data conflicts, data retention working closely with the Data Centre of Excellence Worked with Microsoft Purview and other MDM tools to support data cataloging, lineage and reference data management Business Intelligence & Automation: Proficiency in Power BI, Power Apps, Power Automate, and Microsoft 365 tools Experience designing interactive dashboards and automating business workflows Cloud Security & Governance: Familiarity with Azure Security Center, Azure Monitor, Azure Policy and Azure Backup Experience implementing security best practices and compliance frameworks (POPIA, GDPR) Hands‑on experience with Microsoft Purview and/or other data governance tools Dev Ops & Infrastructure as Code: Experience with Azure Dev Ops, CI/CD pipelines, Terraform, and Machine Learning Ops Ability to manage infrastructure and deployments using automated tooling and Ia C principles Cross‑Functional Collaboration: Demonstrated success working with enterprise solutions architect, data engineers, analysts, developers, and business stakeholders. Experience participating in architecture forums, steering committees, and governance bodies. 5+ years domain knowledge in Insurance (Short Term / Life / Microinsurance / Health Insurance) Experience in aligning data strategies with regulatory and operational needs in the insurance sector Duties & Responsibilities: Architect Scalable Data Platforms: Design and implement enterprise‑grade data architectures using Microsoft Azure technologies including Azure SQL, Synapse, Cosmos DB, Data Lake, Databricks, Py Spark Notebooks and Dataverse Ensure platforms are secure, resilient, and optimized for performance and cost Establish scalable data modelling practices, including conceptual, logical and physical models aligned with business domains Lead Data Modernization Initiatives: Drive the transformation of legacy systems into cloud-native solutions from a data technology perspective Promote the adoption of modern data services and analytics tools across the organization Oversee migration strategies, including schema conversions, data mapping and validation processes Govern Data Lifecycle and Compliance: Define and enforce standards for data sourcing, structuring, validation, storage, and security, working closely with the Data Centre of Excellence Ensure compliance with POPIA, GDPR and internal governance frameworks Assist the business data architect with implementation of metadata management, data cataloging and sensitive data tracking initiatives Support discoverability and lineage tracking Enable Business Intelligence and Analytics: Integrate tools such as Power BI, Azure Analysis Services and Azure Machine Learning to support decision‑making, enabling the Data Teams in the Planning Units of the business Collaborate with business units to deliver actionable insights through data visualization and predictive modeling Support semantic modelling and KPI definitions to ensure consistent reporting across data teams Support Application Development and Integration: Provide architectural guidance for. NET‑based applications and data‑driven solutions working with the Enterprise Solutions Architect Enable seamless integration across Microsoft 365, Power Platform, Dynamics 365 and Share Point / Teams Ensure data contracts are well‑defined for interoperability and reuse Champion Automation and Dev Ops Practices: Implement CI/CD pipelines, infrastructure‑as‑code (Terraform), and automated data workflows using Azure Data Factory and Power Automate Promote Dev Ops culture and tooling across data engineering teams Monitor and optimise ETL pipelines, ensuring observability, reliability and scalability Collaborate Across Teams and Stakeholders: Work closely with enterprise solutions architect, data architect, data engineers, developers, analysts and business teams to align technology with strategic goals Represent the business in architecture forums, steering committees and cloud governance bodies from a data technologies perspective Facilitate cross‑functional data governance and stewardship initiatives Mentor and Develop Talent: Guide junior architects and engineers in best practices and certification pathways Foster a culture of continuous learning and innovation within the data technology space Encourage hands‑on experience with data modelling tools, ETL frameworks and Azure services Ensure Data Quality Management and Observability: Define and implement data quality frameworks to monitor accuracy, completeness, consistency and timeliness across data assets working closely with the Data Architect Implement observability tools such as Azure Log Analytics, Application Insights, Purview to track data lineage, usage patterns and health