Quick overview
Job description
Role: Data Engineer
Location: Princeton, NJ
We re looking for a Data Engineer to design, build, and maintain reliable data pipelines and platforms that power analytics, reporting, and data products across a Property & Casualty (P&C) auto insurance business. You ll partner with actuarial, underwriting, claims, product, finance teams to deliver trusted, well-governed data that supports retention, loss modeling, fraud detection, customer experience.
Essential Job Functions:
- Build and maintain scalable batch and streaming data pipelines (ingestion, transformation, validation, and delivery).
- Integrate data from core insurance systems (policy administration, billing, claims, Contact management system).
- Model and curate analytical datasets (e.g., policy, quote, exposure, premium, loss, claim, payment, reserve, subrogation, salvage).
- Implement data quality checks, anomaly detection, and reconciliation for critical metrics
- Develop and maintain a data lake/warehouse (schema design, partitioning, performance tuning, cost optimization).
- Collaborate with governance, security, and compliance teams to implement access controls, PII handling, retention, and auditability.
- Operate data workflows in production: monitoring, alerting, incident response, SLAs, and root-cause analysis.
- Contribute to engineering best practices: CI/CD, infrastructure-as-code, testing, code reviews, and documentation.
- Perform other duties as assigned.
Experience/Qualifications:
- Bachelor's degree in computer science or technology related is preferred.
- 3+ years of experience in data engineering, Machine learning, with strong SQL skills and experience building dimensional or analytical models.
- Proficiency in at least one programming language: Python, Scala, or Java.
- Experience with modern data warehouses/lakehouses (e.g., Snowflake, BigQuery, Redshift, Databricks, Spark).
- Familiarity with data quality/testing (e.g., dbt tests, Great Expectations) and observability/monitoring patterns.
- Understanding of data security fundamentals (PII, encryption, role-based access control).
Preferred
- Experience in insurance, financial services, or other regulated industries
- Knowledge of P&C auto insurance concepts: underwriting, rating/pricing, claims lifecycle, reserves, exposure, reinsurance is a plus
- Knowledge with event/streaming systems (Kafka, Kinesis, Pub/Sub) and CDC tools (Debezium, Fivetran/HVR, etc.).
- Exposure to MLOps/data needs for fraud detection, pricing, or claims severity models is a plus.
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