Staff Data Engineer

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.

What Success Looks Like

Within 90 days you will have:

30 days:

Completed a deep orientation into the Snowflake platform, existing data models, and governance infrastructure. You understand how data flows through Sixfold today, where the gaps are, and what the CDAO is building toward. You know whose problems you're solving.

60 days:

Made your first meaningful platform contributions. You've identified an area for improvement, proposed an approach, and started executing with team buy-in.

90 days:

Owned a substantive initiative end-to-end — a governance pipeline, a new data model, or a cross-functional build with platform or AI. You're operating with real autonomy and have a clear point of view on what the roadmap should prioritize next.

About You

You have a bachelor's degree

• in Computer Science, Engineering, or a related field, and
• 7+ years of data engineering experience, including senior or lead scope with real architectural ownership.
• Your Snowflake expertise is deep and current: dynamic tables, openflow, replication, masking and row access policies, performance tuning, Snowflake intelligence. You know where the platform's edges are.
• Your technical toolkit is strong: expertise in SQL and Python, and you use generative AI as a natural part of how you build and think, not theoretically.
• You've worked in insurance
• , ideally at a P&C carrier, MGA, reinsurer, or insurtech. You understand the data landscape and terminology: submissions, policy, exposure, and claims. This isn't a nice-to-have.
• You've led architecture decisions and brought others along, engineers and non-engineers alike.
• You're intellectually curious in the way that actually matters: you ask better questions when something doesn't add up, not just when it's easy.
• You've worked within AI/ML governance frameworks and understand what regulatory requirements like GDPR and CCPA actually mean for how data gets stored, accessed, and moved.
• Bonus Points If…
• You've built or operated data platforms across multiple regions and have wrestled with data residency constraints firsthand.
• You've had exposure to customer-facing analytics products and understand what it means when the data you manage is something a customer directly sees and depends on.
• You’ve built a data agent t hat understands multiple data sources and provides actionable insights to make decisions.