Data Architect Fabric Management Lead

Role & Responsibilities Overview:

• Design end to end data architectures using Microsoft Fabric components (Data Factory Lakehouse Warehouse Real Time Analytics OneLake).
• Define data models integration patterns and storage strategies for policy claims billing actuarial and customer data.
• Develop architectural blueprints reference architectures and reusable frameworks aligned with enterprise standards.
• Oversee ingestion pipelines using Fabric Data Factory supporting batch streaming and API based integrations.
• Implement Lakehouse based architectures for scalable analytics and machine learning workloads.
• Ensure data pipelines are optimized for performance cost and reliability.
• Partner with Data Governance teams to enforce data standards lineage metadata and quality rules.
• Implement governance capabilities within Fabric including data catalogs sensitivity labels and access controls.
• Support regulatory compliance for insurance data (e.g. NAIC state regulations privacy laws).
• Collaborate with cloud engineering teams to optimize Fabric deployments within the Microsoft ecosystem (Azure AD Purview Power BI).
• Ensure alignment with enterprise cloud strategy security frameworks and architectural guardrails.
• Evaluate new Fabric features and recommend adoption strategies.
• Work closely with business stakeholders to translate insurance data needs into scalable technical solutions.
• Provide architectural guidance to data engineers analysts and BI developers.
• Lead technical design reviews and ensure architectural consistency across projects.
• Define best practices for Fabric performance tuning storage optimization and cost management.
• Implement robust security models including RBAC data masking and encryption.
• Monitor platform health and proactively address architectural risks.

Candidate Profile:

10 years of experience in data architecture data engineering or analytics platform design.

• Strong hands on experience with Microsoft Fabric and related Azure services.
• Deep understanding of insurance data domains (policy claims underwriting actuarial billing).
• Expertise in data modeling (dimensional canonical semantic models).
• Strong knowledge of data governance metadata management and data quality practices.
• Proficiency with SQL Python and modern data engineering frameworks.
• Excellent communication and stakeholder management skills.
• Experience with Microsoft Purview Power BI Databricks or Azure Synapse.
• Familiarity with modern data architecture concepts (data mesh data fabric Lakehouse).
• Certifications such as Azure Data Engineer Azure Solutions Architect.
• Prior experience in P&C or Life insurance data modernization programs.