About the job:
Data Architect - Data Fabric Management LeadRole & 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.
