Job Description
Location: Princeton, NJ (Hybrid 3 days on-site)
Type: Long Term Contract
Overview
Hybrid, Long Term Contract opportunity supporting a client in the insurance and risk analytics sector. Seeking a highly skilled Data Engineer to lead Azure-based data architecture and support actuarial analytics and reporting functions. Ideal for professionals with deep experience in Microsoft BI, data warehousing, and Azure big data technologies.
Key Responsibilities
Architect and build scalable data pipelines using Azure Data Factory, Databricks, and SQL-based technologies.
Design and implement data layers (staging, bronze, silver, gold) in a robust data lake architecture.
Develop and schedule Azure Analysis Services tabular models and cubes via Automation Runbooks.
Support business intelligence efforts through development of tabular/multidimensional SSAS cubes and custom reporting metrics (KPIs, partitions, data mining models).
Translate business logic into ETL workflows across varied data sources and formats.
Collaborate with cross-functional teams using Agile and SCRUM methodologies to support advanced analytics projects.
Required Skills & Experience
10+ years of experience in data engineering and business intelligence architecture.
Deep hands-on experience with Azure services including:
Data Factory (ADF)
Databricks
Analysis Services (SSAS)
Azure SQL and Data Lake tools
Integration and Reporting Services (SSIS, SSRS)
Proficient in building notebooks to support raw-to-curated data processing.
Strong understanding of normalization/de-normalization and data warehouse design principles.
Experience supporting actuarial systems, pricing models, and reporting workflows is a plus.
Preferred Domain Knowledge
Insurance or actuarial data environments
Familiarity with reinsurance structures, client hierarchies, and analytics-ready data
Experience developing tools that feed downstream broker reporting and actuarial pricing functions
Work Authorization & Additional Info
No relocation assistance provided
No visa sponsorship available
Must be able to work onsite 3 days/week in Princeton, NJ