Quick Summary

You're the technical anchor for an analytics engineering team-owning ontology design, semantic modeling, and the patterns your team builds on. 8+ years required.

The opportunity

We're looking for a Staff Analytics Engineer to be the technical anchor of one of Kin's analytics engineering teams - the person who makes your team's slice of our shared data model correct, durable, and trusted.

Within the Data Engineering organization, Analytics Engineering turns raw, domain-owned data into a shared, trusted semantic model of the business. As Kin moves to a data mesh - where domain teams own their data as products on a shared, self-serve platform - and adopts an ontology-driven source of truth, each analytics engineering team owns a meaningful piece of that model. You'll own the hardest modeling and design problems in your team's scope, from the ontology objects that represent your slice of the business to the dimensional and semantic models that serve them downstream in BI and self-service. You'll also be a technical thought partner to the product and business leaders your team supports - going deep enough on their goals to turn ambiguous needs into clear, durable technical plans. Understanding the business is part of the craft here, not someone else's job.

Your responsibilities

• Own the hardest modeling and architecture in your team's scope - ontology objects (types, properties, link types, and actions) that model your part of the business as it actually operates, and the dimensional and semantic models (e.g., Looker/LookML) that serve them downstream
• Act as a technical thought partner to the product and business leaders your team supports: understand their goals deeply and translate ambiguous or conflicting business needs into clear, durable technical plans
• Take end-to-end ownership of your team's most business-critical initiatives, where deep semantic and architectural judgment is the differentiator
• Align your team's models with shared representations of core entities (customer, policy, claim) so they stay consistent and interoperable across the mesh - partnering with the Principal Engineer and peers where definitions are cross-cutting
• Define the modeling patterns, naming conventions, and reference implementations your team builds on, and contribute them back to the discipline's shared standards
• Drive data-as-a-product expectations within your team's scope - ownership, contracts, documentation, and reliability for what your team owns
• Partner with domain data engineers to shape the data contracts and pipelines that feed clean, well-defined ontology objects, and surface upstream issues that degrade your team's models
• Raise the technical bar through model and design review, pairing, mentorship, and contributions to hiring and onboarding
• Set your team's patterns for applying Claude and Claude Code to analytics engineering work, and design the ontology and semantic layer to be AI-consumable so tools like Databricks Genie can reason over your team's data reliably

Success in this role

In your first 6-12 months at Kin, success is less about checking boxes and more about the impact you create. You'll use your skills and judgment to take ownership of meaningful work, improve how we operate, and help move Kin's mission forward. Along the way, you'll deliver outcomes that make a real difference for both Kinfolk and the homeowners we serve.

By the end of your first year, you should feel confident in your role, trusted as an owner, and proud of the progress you've helped make.

• The hardest modeling problems in your team's scope are solved durably - your team's ontology objects and presentation-layer models are stable, documented, and trusted by the business partners who depend on them
• Product and business partners bring you in early on their hardest problems and trust the technical direction you set
• Your team builds on the patterns you've established without needing your review on routine work, measurably reducing bottlenecks
• A previously intractable modeling problem in your team's domain is solved and documented as a reference others across the mesh can follow

What you'll bring

• 8+ years in analytics engineering, BI engineering, or data modeling roles, with a track record of being the technical anchor on complex, cross-cutting data work
• Deep expertise in semantic and data modeling - and the judgment to know when an ontology-driven model, a dimensional model, or both is the right tool
• Hands-on experience with an ontology or object-based semantic layer (e.g., Palantir Foundry Ontology), or strong transferable modeling experience and the appetite to go deep
• Fluency in dimensional modeling for presentation/BI consumption (e.g., Looker/LookML) downstream of a source-of-truth model
• Experience with data mesh, data-as-a-product, and domain-oriented architecture - or strong, well-reasoned conviction about how federated data ownership should work
• Experience with modern lakehouse platforms (e.g., Databricks) operated as a shared, self-serve data platform
• Demonstrated technical leadership and influence without formal authority - you move a team and its partners through credibility, clarity, and example
• Strong written and verbal communication, especially when navigating ambiguity, tradeoffs, or disagreement
• Comfort applying Claude, Claude Code, and Databricks-native AI tools in day-to-day analytics engineering work

Bonus if you have:

• Python, Git-based workflows, or transformation frameworks such as SQLMesh or dbt
• Experience with Foundry Pipeline Builder/Functions or performance tuning at scale

How we hire

We believe a great hiring experience should be clear, respectful, and human. We'll accept applications for this position until July 24, 2026. While our recruiting team uses AI tools for efficiency, resumes are still screened by Kin's in-house recruiters, and candidate evaluations and hiring decisions are made by recruiters and hiring teams. Rest assured, real people make real decisions.

The hiring process and timeline for each role will vary, depending on the position. However, here are some things you can expect from us:

• Prompt updates and feedback following interviews
• Interviews with recruiters, hiring managers, and members of teams
• Skills assessment relevant to the position, if applicable
• Genuine, thoughtful human interaction at every step

How we support you

We offer a comprehensive, competitive benefits program, allowing you to choose the benefits that are best for you and your family, starting on the first day of the month following your start date.

Core Benefits

• Competitive salary and company equity through Restricted Stock Units (RSUs), granted as part of our standard compensation package and based on role and level
• 401(k) with company match up to 4% of eligible earnings
• Multiple medical plan options, plus dental and vision coverage
• Company-funded HSA contributions (based on medical plan selection)
• Company-paid life insurance and short-term disability

Health & Wellbeing

• A variety of supplemental benefit options, including long-term disability, critical illness, accident, legal, and pet insurance
• Access to mental health support and confidential counseling resources
• Flexible PTO for exempt employees (most employees take 15-20 days per year), plus 8 company-observed holidays
• Paid parental leave, including up to 14 weeks at 100% pay for birthing parents and 8 weeks at 100% pay for non-birthing parents

Growth & Development

• Career mobility and internal growth opportunities across the organization
• Professional development budgets for certifications, conferences, and learning available, subject to management approval

Where we work

We are a remote-first company with offices in Chicago, IL and St. Petersburg, FL where teams can come together for collaboration.

For Sales Agents and Customer Service Agents: These roles sit in any of the following 30 states: AL, AZ, CO, FL, ID, IL, IN, KS, KY, MA, MD, ME, MI, MO, MT, NC, NE, NM, NV, NY, OH, OK, PA, SC, TN, TX, UT, VT, VA, WA, and WI.

For all other positions, these roles can sit in any of the following 40 states: AL, AR, AZ, CA (exempt only), CO, CT, FL, GA, ID, IL, IN, IA, KS, KY, MA, ME, MD, MI, MN, MO, MT, NC, NE, NJ, NM, NV, NY, OH, OK, OR, PA, SC, SD, TN, TX, UT, VT, VA, WA, and WI. Please only apply if you are able to live and work full-time in one of the states listed above.

For remote technical positions located in Canada, we are only able to hire individuals who reside in Ontario. Applicants must be able to live and work full-time in Ontario to be considered.

State locations and specifics are subject to change as our hiring requirements shift.