Data Engineer

Data EngineerLocation: NYC- 3 days on site downtown NYC (final onsite interview)Duration: It might get extended past 6 monthsKey Responsibilities:Design, develop, and maintain data marts tailored to the specific needs of the insurance business.Develop scalable ETL/ELT pipelines using Fabric Data Factory (Pipelines and Dataflows Gen2) and PySpark Notebooks. Optimize Fabric Spark runtimes for large-scale data processing.Strong focus on data integrity, performance tuning, idempotency, cost analysis, testing, and risk mitigation.Develop and optimize complex T-SQL queries, stored procedures, and views for high-performance data access.Collaborate with the Data Analytics team to deliver actionable insights to the business utilizing Power BI’s semantic layer, including custom KPIs using DAX.Ensure data quality, consistency, and governance across all data layers.Document data models, business logic, and technical specifications to ensure reliability and transparency.Stay current with Azure technologies and insurance data trends to drive continuous improvement.Required Qualifications:Bachelor’s or Master’s degree in Computer Science, Information Systems, or a related discipline.5+ years of experience in data engineering, analytics, or BI roles.Strong hands-on experience with Microsoft T-SQL, Azure Synapse Analytics, Power BI Semantic Layer (or SSAS) and Azure Data Factory.Proficiency in Python/PySpark. Experience with DAX is a strong plus.Experience with Git, branch management, and CI/CD pipelines in a data environment.Deep understanding of P&C insurance industry data (e.g., policy administration, claims processing, underwriting, actuarial models, ceded reinsurance).Working knowledge of insurance enterprise data models such as ACORD, IBM, etc.Experience with data warehousing, dimensional modeling, and data architecture.Proven ability to optimize performance in large-scale data environments.Excellent communication and collaboration skills with both technical and business stakeholders.Ability to manage concurrent deliverables in a fast-paced environment