Data Engineer
US$155,000 – US$195,000 / yr base salary
Posted 19 May 2026
Advertised as “Staff Data Engineer”
BranchFactor Summary
The original posting with the fluff stripped out
- Expected experience
- 7+ yrs
- Management level
- Individual contributor
- Employment
- Remote
- Visa sponsorship
- Not offered
| Base salary | US$155,000 – US$195,000 / yr |
|---|
Field of studyComputer Science, Engineering (or related)
Study levelBachelor's
Senior Data Engineer
Insurance underwriting runs on human judgment, manual workflows, and knowledge locked in someone's head. It breaks when that person leaves and doesn't scale when the book doubles.
Sixfold is building AI agents that understand risk the way a 20-year veteran underwriter does. Not summaries or flags, but systems that make real decisions on billions in premium for some of the world's largest carriers. AI is the product and the workflow. The Senior Data Engineer makes sure the data powering those decisions is trusted, governed, and built to scale.
If you live and breathe Data and AI tools, understand how models work under the hood, and can translate that into business outcomes for a room full of skeptical underwriters, this role was written for you.
Who We Are
🏔 Product: Sixfold is the AI brain for underwriting. Our platform handles submissions at scale, assessing risk against appetite, surfacing cited insights, and deploying AI agents to handle triage, research, and referrals so underwriters can focus on building profitable portfolios.
💪 Team: A focused team of insurance operators, AI researchers, and engineers who love hard problems. We're pushing the boundaries of AI adoption across every function, from how we build, to how we sell and to how we support customers. We ship fast and stay close.
📈 Traction: Processing billions in premium for some of the world's largest carriers. We know AI. We know underwriting. We're building what comes next.
About the Role
In this role, you will:
- Lead data platform strategy and execution. Partner with the CDAO to shape overall data strategy and translate it into engineering roadmaps with clear owners, timelines, and outcomes. You're not inheriting a finished system — you're making consequential architectural decisions that compound over time.
- Own the Snowflake data lake end to end. Develop, maintain, and evolve the platform and its associated services — from ingestion to serving. This includes architecting data models and patterns that support analytics, AI/ML pipelines, and customer-facing products.
- Build governance that actually works. Design and operate pipelines covering data quality, lineage, access control, and regulatory requirements. Governance here isn't a checkbox — it's infrastructure.
- Drive cross-functional data initiatives. Collaborate with platform engineering, AI, and product teams to move shared priorities forward. You're the connective tissue between data infrastructure and the rest of the org.