Principal Data Engineer

Senior Director, Data Engineering

Hybrid – New York, NY

Base Salary: $200,000 – $250,000 bonus, 401(k) match, comprehensive benefits

About the Opportunity

A leading global property & casualty insurer is seeking a senior data engineering leader to drive the evolution of its enterprise data environment. This role sits at the intersection of technology and core insurance operations, enabling critical functions such as underwriting, claims, finance, risk, and regulatory reporting through modern, scalable data solutions.

This individual will play a pivotal role in modernizing a complex data landscape—transitioning fragmented, regionally siloed systems into cohesive, enterprise-grade platforms that deliver timely, accurate, and actionable insights.

Position Summary

This role is accountable for defining and executing the strategy for enterprise data engineering, with a focus on building resilient, high-performing data platforms and pipelines. You will lead efforts to streamline data integration, enhance processing capabilities, and elevate data quality standards across the organization.

A key priority will be simplifying legacy environments and enabling more frequent, automated data flows to support financial and actuarial processes, including accelerating close cycles and improving reporting accuracy.

Core Responsibilities

Enterprise Data Platforms & Integration

• Lead the design and implementation of scalable data pipelines that unify and standardize data across multiple business domains
• Drive consolidation of legacy and regional data stores into centralized, enterprise-wide platforms
• Develop and maintain high-performance data warehouses and data marts aligned to business and regulatory needs

Operational Efficiency & Automation

• Modernize financial and actuarial data workflows through automation and improved data orchestration
• Transition batch-based processes to more frequent or near real-time data processing models
• Enhance the speed and reliability of key reporting cycles, including month-end close

Data Integrity & Governance

• Establish robust frameworks for monitoring, validating, and improving data quality
• Implement traceability, lineage, and reconciliation processes to ensure transparency and auditability
• Promote best practices in data governance, security, and compliance

Platform Simplification & Transformation

• Evaluate the current data ecosystem to identify redundancy and inefficiency
• Lead initiatives to retire outdated systems and migrate to strategic, scalable platforms

Stakeholder Partnership

• Work closely with business leaders and technical teams to translate requirements into impactful data solutions
• Ensure alignment between engineering delivery and business priorities
• Support adoption of new tools, platforms, and processes across the organization

Leadership & Team Development

• Build and lead a distributed team of data engineers, fostering technical excellence and domain expertise
• Develop team capabilities across modern data technologies and insurance data modeling
• Create a culture of accountability, innovation, and continuous improvement

Architecture & Standards

• Collaborate with enterprise architecture teams to ensure alignment with broader technology standards
• Enforce best practices in system design, performance, and data security (including sensitive data handling)

Performance & Risk Management

• Define and track KPIs to measure platform performance and delivery effectiveness
• Identify risks and implement controls to ensure stability and scalability of data solutions

Qualifications & Experience

• 12 years of experience in data engineering, data platforms, or data integration, with at least 5 years in leadership roles
• Proven success delivering large-scale data transformation initiatives, including system consolidation and migration
• Deep experience within the insurance industry, particularly across financial, actuarial, and operational data domains
• Strong expertise in SQL and enterprise data tools (e.g., Informatica, SSIS) as well as modern cloud-based platforms (e.g., Databricks, Azure-based ecosystems)
• Experience building and optimizing data pipelines, warehouses, and data models at scale
• Demonstrated ability to implement data quality, validation, and reconciliation frameworks
• Strong understanding of insurance systems and data structures (policy, claims, finance, reinsurance)
• Track record of building and leading high-performing technical teams

Education

• Bachelor’s degree in Computer Science, Information Systems, or a related field required
• Advanced degree preferred

Additional

• Relevant certifications in cloud platforms or data engineering are a plus