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Data Engineer

TALENDICA
1 day ago
Full-time
On-site
New York, NY

Data Engineer

Location: NYC- 3 days on site downtown NYC (final onsite interview)

Duration: It might get extended past 6 months

Key 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