Azure Data Engineer

Role & Responsibilities Overview:

• Build and maintain Azure/Microsoft Fabric data pipelines (batch, streaming, API) using Data Factory, Lakehouse, Warehouse, and Real‑Time Analytics.
• Design scalable data models and ETL/ELT workflows supporting insurance datasets (policy, claims, billing, actuarial, customer).
• Implement Lakehouse‑based architectures enabling analytics, reporting, and ML workloads.
• Optimize pipeline performance, reliability, cost, and storage across Azure and Fabric environments.
• Apply data governance, lineage, metadata, and data quality rules in collaboration with governance teams.
• Implement security and compliance controls (RBAC, sensitivity labels, encryption) aligned with NAIC and data privacy regulations.
• Collaborate with cloud engineering, security, and business stakeholders to deliver robust, standards‑aligned solutions.
• Support platform monitoring, troubleshoot issues proactively, and contribute to continuous improvement and Fabric feature adoption.

• 7+ years of experience in data architecture, data engineering, or analytics platform design.
• Strong hands on experience of at least 5 years with Azure services.
• Deep understanding of P&C 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.
• Prior experience in P&C insurance data modernization programs.