VP, Data Engineering
Location: Morristown, NJ (Hybrid, 3 days on site)
Salary: $197,000 – $275,000 + 30% Bonus
We’re partnered with a growing, innovation-focused insurance organization that is investing heavily in modern data capabilities. This is a high-impact leadership role for someone who thrives at the intersection of hands-on engineering, platform modernization, and business alignment.
You’ll play a critical role in transforming legacy data environments into a scalable, cloud-native ecosystem, enabling faster insights, stronger governance, and more reliable data products across the enterprise.
What You’ll Do
Lead Data Platform Transformation
- Drive migration from legacy data warehouses and datamarts to a modern AWS-based analytics platform
- Re-architect transformation logic into scalable, modular ELT pipelines
- Establish enterprise standards for data modeling aligned to core insurance domains
- Oversee structured cutover and decommissioning of legacy systems
Build World-Class Data Engineering Practices
- Implement CI/CD frameworks for data pipelines, ensuring repeatable and reliable deployments
- Introduce DataOps best practices including automated testing, validation, and release governance
- Define coding standards, version control strategies, and deployment workflows
Design Scalable, Reliable Data Pipelines
- Architect high-performance batch and incremental data pipelines
- Implement orchestration, monitoring, alerting, and failure recovery mechanisms
- Optimize performance and cost efficiency within cloud data platforms
Drive Data Quality & Observability
- Establish robust data quality frameworks across completeness, accuracy, and timeliness
- Implement monitoring and observability metrics to ensure SLA adherence and system health
- Partner with governance teams to support lineage, auditability, and compliance
Partner Across the Business
- Collaborate with underwriting, claims, actuarial, and finance teams to deliver trusted data products
- Align data models and KPIs to business needs
- Enable advanced analytics and modeling through strong data foundations
Qualifications
- 10+ years of experience in data engineering, including leadership of large-scale data initiatives
- Proven background in the insurance industry (required)
- Strong expertise in Python and SQL for data engineering and pipeline development
- Hands-on experience building and optimizing ETL/ELT pipelines at scale
- Deep knowledge of AWS data services (e.g., Redshift, S3, IAM, orchestration tools)
- Experience migrating legacy data environments to modern cloud platforms
- Demonstrated success implementing CI/CD and DataOps practices
Preferred
- Experience with transformation frameworks like dbt
- Familiarity with data quality and validation tools (e.g., Great Expectations)
- Infrastructure-as-Code experience
- Exposure to data observability platforms
- Understanding of regulatory and audit requirements in insurance
