Data Engineer Job at Blackstar, Princeton, NJ

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  • Blackstar
  • Princeton, NJ

Job Description

About the Role:

Join the company, McLennans Technology Group (MMC Tech), as a Data Engineer supporting Guy Carpenter's global actuarial modernization initiative. We're transforming how data drives analytics, pricing tools, and reinsurance reporting across thousands of clients and analysts worldwide. If you're passionate about building robust, scalable data pipelines and working with cutting-edge Azure technologies, this is your next big opportunity.

Key Responsibilities:

  • Design, develop, and maintain end-to-end data pipelines using Azure Data Factory, Databricks, and Data Lake .
  • Build and manage data warehouse layers (staging, bronze, silver, gold) and ensure reliable data flow across systems.
  • Implement complex ETL/ELT processes for structured and unstructured data.
  • Develop and deploy Azure Analysis Services (SSAS) tabular models and schedule with Azure Automation Runbooks .
  • Support data modeling, performance tuning, and analytics for actuarial and business intelligence teams.
  • Collaborate with cross-functional teams following Agile/SCRUM methodologies.

Must-Have Technical Skills:

  • Microsoft Azure BI Stack : Azure Data Factory (ADF), Azure Databricks, Azure Data Lake Analytics, ADLS, Azure Analysis Services (SSAS), Azure Integration Runtime.
  • Data Tools : DBT, Azure Event Hubs, Stream Analytics, SQL Server Integration Services (SSIS), SQL Server Reporting Services (SSRS).
  • Databases : Azure SQL, MongoDB, PySpark.

  • Strong understanding of data normalization, denormalization , and warehouse design principles.

Preferred Experience:

  • Experience with reinsurance or insurance domain especially data hierarchies, treaty structures, placements, client tiers, and actuarial inputs/outputs.
  • Built pipelines supporting actuarial rating, analytics, pricing tools , or reporting functions for brokers and clients.
  • Exposure to actuarial tools and understanding of reinsurance workflows is a strong plus.

Apply now if you're ready to shape the future of data engineering in a global organization using advanced Azure tech!

Job Tags

Full time, Worldwide,

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