Data Engineer II (AWS, Python, LLM/RAG, NoSQL, React.js)

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 160 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

Data Analytics, Technology

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

$123,000.00 - $203,000.00

Target Openings

1

What Is the Opportunity?

Travelers Data Engineering team constructs pipelines that contextualize and provide easy access to data by the entire enterprise. As a Data Engineer, you will play a key role in growing and transforming our analytics landscape. In addition to your strong analytical mind, you will bring your inquisitive attitude and ability to translate stories found in data by leveraging a variety of data programming techniques. You will leverage your ability to design, build and deploy data solutions that capture, explore, transform, and utilize data to support Artificial Intelligence, Machine Learning and business intelligence/insights.

What Will You Do?

• Build and operationalize complex data solutions, correct problems, apply transformations, and recommending data cleansing/quality solutions.
• Design complex data solutions
• Perform analysis of complex sources to determine value and use and recommend data to include in analytical processes.
• Incorporate core data management competencies including data governance, data security and data quality.
• Collaborate within and across teams to support delivery and educate end users on complex data products/analytic environment.
• Perform data and system analysis, assessment and resolution for complex defects and incidents and correct as appropriate.
• Test data movement, transformation code, and data components.
• Perform other duties as assigned.

What Will Our Ideal Candidate Have?

• Bachelor’s Degree in STEM related field or equivalent

• Eight years of related experience

• Proficiency in Python for backend development and library/package design

• Experience with API development and integration (e.g., REST, GraphQL)

• Working knowledge of Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) architectures

• Experience with vector databases (e.g., Pinecone, FAISS, Weaviate)

• Experience with NoSQL databases (e.g., MongoDB, DynamoDB, Redis)

• Strong experience with React.js

• Familiarity with modern frontend tooling (e.g., Webpack, Vite, Babel)

• Ability to build responsive and accessible UIs using JavaScript/TypeScript, HTML, and CSS

• Proficiency with AWS services (e.g., Lambda, S3, ECS/EKS, API Gateway, CloudWatch)

• Experience deploying applications in Kubernetes

• Infrastructure-as-Code using Terraform

• CI/CD pipeline setup with GitHub Actions

• Experience with unit testing, integration testing, and end-to-end testing

• Familiarity with frameworks like pytest, Jest, or Playwright

• Adherence to software engineering best practices and design patterns

• Strong knowledge of Git and experience using GitHub for team collaboration and code reviews

• Familiarity with agile development practices and tools (e.g., Jira, Notion)

• Experience optimizing or fine-tuning LLMs or working with LangChain

• Knowledge of event-driven architectures or serverless frameworks

• Background in data pipelines, ETL, or stream processing

• Exposure to observability tools (e.g., Prometheus, Grafana, Datadog)

• Highly proficient use of tools, techniques, and manipulation including Cloud platforms, program