Position: Data Engineer Location: USA, New Jersey (Hybrid – Onsite 3 Days/Week) Overview We are seeking a skilled and motivated Data Engineer to join our client's team in NJ, working on-site three days a week. This role focuses on designing, building, and optimizing scalable data pipelines and business intelligence solutions within the Azure ecosystem. Key Responsibilities: • Design, develop, and maintain scalable data pipelines using Azure Data Factory and Azure Databricks. • Build, transform, and optimize data across multiple layers—staging, bronze, silver, and gold zones. • Develop Databricks notebooks to process data from raw ingestion through to curated output layers. • Implement robust ETL processes across both homogeneous and heterogeneous systems using Azure BI tools. • Develop and deploy tabular models with Azure Analysis Services and automate deployments with Azure Automation Runbooks. • Create and manage SSAS cubes (tabular and multidimensional), including KPIs, measures, aggregations, partitions, and data mining models. • Collaborate with stakeholders to build data solutions that support actuarial analytics, pricing models, and broker/client-facing reporting tools. • Maintain data warehouse environments and support the entire lifecycle from architecture through deployment and ongoing enhancements. • Participate in Agile development teams, contributing to sprint planning, reviews, and collaborative problem-solving. • Ensure high-quality documentation and adherence to SDLC practices. Key Qualifications: Technical Skills: • Strong hands-on experience with Microsoft Azure BI stack: Azure Data Factory (ADF), Azure Databricks, Azure Analysis Services (SSAS), Azure Data Lake Analytics, Azure Data Lake Store (ADLS) • Azure Integration Runtime, Event Hubs, Stream Analytics, DBT • Proficiency in database technologies including: Azure SQL, MongoDB, PySpark • Deep understanding of data modeling, normalization/denormalization techniques, and data warehouse architecture. • Expertise in developing and maintaining ETL processes and managing multi-layered data environments. Preferred Domain Experience: • Prior experience in the insurance or actuarial domain is highly desirable. • Familiarity with reinsurance broking data such as placements, treaty structures, renewal workflows, and client hierarchies. • Understanding of actuarial rating inputs/outputs including experience and exposure data, program layers, and data tags. • Experience creating pipelines that support actuarial systems, pricing analytics, and reporting dashboards.