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# Data & Analytics Engineer with P&C insurance in NYC(F2F interview)

- **Company:** Amtex Systems Inc
- **Location:** Mundelein, IL, United States
- **Experience:** Expert
- **Contract:** Temporary contract
- **Skills:** Big Data, Information Systems, Data Architecture, Information Engineering, Data Systems, Data Warehousing, Dimensional Modeling, Python (Programming Language), Power BI, SQL Server Analysis Services, Transact-SQL, Azure Data Factory, Git, Pyspark, Information Technology, Data Analytics, Azure Synapse Analytics
- **Published:** November 7, 2026
- **Apply:** https://www.thejobnetwork.com/job/b2264e83-1c07-42d0-9b5f-7753849e68a2/data-analytics-engineer-with-pc-insurance-in-nycff-interview

## About the Role

Client is looking for a highly skilled Senior Data & Analytics Engineer with a strong technical background and deep understanding of the P&C insurance Industry. This role is critical in designing and delivering scalable, high-performance data solutions that empower analytics, reporting, and strategic decision-making. The ideal candidate will have expertise in Microsoft T-SQL, Azure Synapse Analytics, Azure Data Factory (ADF) and Power BI semantic layer, along with a solid grasp of insurance data domains such as policy, claims, underwriting, and actuarial., * Bachelor's or Master's degree in Computer Science, Information Systems, or a related discipline.
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 * 5+ years of experience in data engineering, analytics, or BI roles.
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 * Strong hands-on experience with Microsoft T-SQL, Azure Synapse Analytics, Power BI Semantic Layer (or SSAS) and Azure Data Factory.
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 * Proficiency in Python/PySpark. Experience with DAX is a strong plus.
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 * Experience with Git, branch management, and CI/CD pipelines in a data environment.
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 * Deep understanding of P&C insurance industry data (e.g., policy administration, claims processing, underwriting, actuarial models, ceded reinsurance).
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 * Working knowledge of insurance enterprise data models such as ACORD, IBM, etc.
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 * Experience with data warehousing, dimensional modeling, and data architecture.
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 * Proven ability to optimize performance in large-scale data environments.
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 * Excellent communication and collaboration skills with both technical and business stakeholders.
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 * Ability to manage concurrent deliverables in a fast-paced environment.
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