Gen AI - Data Engineer II at Travelers Insurance Company
Atlanta, GA
$126,500–$208,700from the description
Aug 4, 2026
Atlanta, GA
Sep 24, 2026
What this job asks for AI summary
A data engineering role at a large property-casualty insurer, focused on designing, building, and operationalizing complex data pipelines that support AI/ML and business intelligence workloads across the enterprise. The position involves data transformation, quality, governance, and the application of Generative AI concepts such as RAG and agentic frameworks. It suits an experienced data engineer comfortable working across cloud platforms and collaborating with cross-functional teams.
Senior level · 8+ years · Bachelor's required · Full-time
We read this from the posting text with AI. Skim the description below before ruling yourself out.
How this req sits in the market our data
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $142,568 (middle half $111,775–$173,013). This posting is about at that midpoint.
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Aug 6, 2026. It is a model, not a headcount.
Why we read it this way (4)
The hard requirements section ('What is a Must Have?') specifies a Bachelor's degree in CS or related STEM field and 4 additional years of data engineering experience on top of the 8 years of related experience mentioned in the ideal candidate section. The 8-year figure is used as the overall years minimum since it represents the broader stated experience expectation.
Cloud platforms are required per the ideal candidate section with firm language ('highly proficient use of tools, techniques... including Cloud platforms'), but no specific cloud provider (AWS, Azure, GCP) is named.
Gen AI concepts (RAG, LLMs, Agentic Frameworks, chunking, hyperparameters) appear under the preferred 'ideal candidate' section rather than the hard 'Must Have' section, so they are marked as preferred.
The role sits at the boundary between data pipeline/architecture work (15-1243) and general software development (15-1252); the emphasis on designing and building data pipelines and data solutions for AI/ML slightly favors 15-1243, but the full-stack and software engineering framing is a meaningful secondary signal.
Read the full posting
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