Staff Analytics Engineer

Job not on LinkedIn

🔥 2 minutes ago

🏈 Alabama, Alaska, +41 more states – Remote

🏈 Alabama – Remote 🐻 Alaska – Remote 🌵 Arizona – Remote 🏄 California – Remote ⛰️ Colorado – Remote 🦌 Connecticut – Remote 🐊 Florida – Remote 🌺 Hawaii – Remote 🥔 Idaho – Remote 🌽 Illinois – Remote 🌾 Iowa – Remote 🌪️ Kansas – Remote 🐎 Kentucky – Remote 🦞 Maine – Remote 🦬 Montana – Remote 🌾 Nebraska – Remote 🎰 Nevada – Remote 🗻 New Hampshire – Remote 🏖️ New Jersey – Remote 🌶️ New Mexico – Remote 🗽 New York – Remote 🌲 North Carolina – Remote 🌾 North Dakota – Remote 🏈 Ohio – Remote 🌲 Oregon – Remote 🦀 Maryland – Remote 🍂 Massachusetts – Remote ❄️ Minnesota – Remote 🎸 Mississippi – Remote 🏰 Missouri – Remote 🔔 Pennsylvania – Remote ⚓ Rhode Island – Remote 🌴 South Carolina – Remote 🗿 South Dakota – Remote 🎸 Tennessee – Remote 🤠 Texas – Remote ⛷️ Utah – Remote 🍁 Vermont – Remote ⚔️ Virginia – Remote ☕ Washington – Remote ⛰️ West Virginia – Remote 🧀 Wisconsin – Remote 🦬 Wyoming – Remote

💵 $159k - $187k / year

⏰ Full Time

🔴 Lead

📊 Analytics Engineer

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Kin Insurance

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2016

💸 Finance

👥 B2C

Finance • B2C

Kin Insurance is a digital insurance company that offers homeowners, landlord, condo, mobile home, high-value home, flood, and auto insurance, along with mortgage products such as home loans, refinancing, home equity loans, and HELOCs. Kin emphasizes affordable, easy online quoting and policy management, claims support, and customer service, operating directly to consumers across multiple U. S. states.

📋 Description

• 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

🎯 Requirements

• 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

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