Note • If shortlisted, we will contact you via email or WhatsApp – kindly respond at the earliest. • This is a W2 position, not a C2C opportunity. • Candidates must be authorized to work in the U.S. (No visa sponsorship provided). Work Type: Contract (6 Months) | Location: Princeton, NJ (Hybrid) Compensation: Hourly (Contact for details) Visa Status: Must be authorized to work in the US (No sponsorship) Job Summary We are seeking an experienced Data Engineer to support actuarial and insurance analytics solutions. You’ll design and implement modern Azure BI pipelines and contribute to data modeling and transformation projects across the insurance domain. Key Responsibilities • Build and maintain data pipelines using Azure Data Factory and Databricks • Develop Azure BI solutions (ADF, SSAS, DBT, SQL, Data Lake) • Design ETL frameworks from staging to gold layer • Support actuarial data modeling and reporting layers • Implement business rules and transformations using PySpark and U-SQL • Collaborate with business teams to gather and translate requirements • Work closely with offshore/onsite team members in Agile settings • Perform unit testing, troubleshooting, and performance tuning • Create and maintain documentation for processes and data workflows Technical Requirements (Must-Have) • Strong experience with Azure Data Factory, Databricks, SSAS, Azure SQL • Hands-on with ETL/BI tools: DBT, SSIS, SSRS • Experience with PySpark, MongoDB, and data lake architecture • Familiarity with insurance or actuarial data structures • Experience in staging/bronze/silver/gold layer modeling • Proficient in creating and scheduling tabular models in Azure • Ability to build scalable, reusable pipelines and data frameworks • Strong SDLC and Agile practices, version control familiarity • Excellent documentation and communication skills Preferred Experience • Prior experience in insurance, actuarial analytics, or reinsurance data • Knowledge of Metarisk, rating tools, and data hierarchies in insurance • Exposure to Azure Event Hubs, Stream Analytics, or CI/CD tools • Strong collaboration and communication with both technical and business users