Job Description

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.