Data Engineer II (AWS, Python, SQL)
TravelersAbout the role
Who Are We?
Taking care of our customers, our communities and each other. That’s the Travelers Promise. By honoring this commitment, we have maintained our reputation as one of the best property casualty insurers in the industry for over 170 years. Join us to discover a culture that is rooted in innovation and thrives on collaboration. Imagine loving what you do and where you do it.
Job Category
Compensation Overview
The annual base salary range provided for this position is a nationwide market range and represents a broad range of salaries for this role across the country. The actual salary for this position will be determined by a number of factors, including the scope, complexity and location of the role; the skills, education, training, credentials and experience of the candidate; and other conditions of employment. As part of our comprehensive compensation and benefits program, employees are also eligible for performance-based cash incentive awards.
Salary Range
$126,500.00 - $208,700.00Target Openings
What Is the Opportunity?
You’ll build deep domain expertise in Property and GL while contributing to modernization efforts and future-facing pricing capabilities. Through complex, high-visibility initiatives, your work will strengthen data reliability, model readiness, and long-term scalability across pricing platforms.
The ideal candidate is motivated by solving complex data engineering problems and collaborating across functions. Your contributions will help advance Travelers’ pricing strategies in a dynamic and evolving insurance marketplace.
What Will You Do?
Own and deliver data pipeline development and ongoing support for Property and GL pricing use cases
Lead model implementation for Property and GL pricing models in partnership with Data Science and Actuarial teams
Build and serve as the GL data subject matter expert to support benchmarks, modernization initiatives, and future enhancements
Provide project leadership, planning, and execution across Property and GL data engineering initiatives
Execute complex data preparation activities, including exploration, cleansing, and transformation, with awareness of enterprise architecture, platforms, and downstream consumption patterns
Translate actuarial and data science requirements into scalable, production-ready data solutions
Adopt and embed MLOps practices across the model development and implementation lifecycle
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