Job description

WHAT WE DO Build the insurance behind the physical world. The world is building data centers, energy projects, hospitals, schools, and critical infrastructure. Every one of those projects needs insurance to move forward. Yet the process of getting that insurance still depends on scattered documents, manual work, and weeks of back-and-forth. Shepherd is rebuilding commercial insurance with software, data, AI, and deep underwriting expertise. We started in construction and energy, where understanding the specifics of a project matters and better decisions have consequences far beyond a screen. We develop insurance products, decide which risks to insure and how to price them, and partner with established insurers to back the coverage. We own the platform our team uses to turn complex submissions into coverage for the builders and operators shaping the world around us. Real problems. Real ownership. Our engineers, designers, underwriters, and actuaries build together. The problems span turning messy documents into reliable data, making pricing more precise, and designing AI agents that can take on increasingly complex underwriting work. The ambition is a platform where experts spend more time on judgment and relationships, supported by software that handles the work around them. Join us to build systems whose decisions help real projects get built. 630+ customers / $500B+ insured project value [app.ashbyhq.com] OUR INVESTORS Capital to build. Partners to grow with. $67M total funding / $42M Series B in March 2026 Shepherd is backed by Intact Private Capital, Costanoa Ventures, Spark Capital, Susa Ventures, and Y Combinator. In March 2026, we announced a $42M Series B led by Intact Private Capital, bringing our total funding to $67M. Intact is also a capacity partner. Alongside its investment, Intact works with Shepherd to bring insurance products to market. That relationship connects our platform and underwriting expertise with the resources of a global insurer. A bigger opportunity ahead We are investing in new insurance products, our underwriting team, and the path toward autonomous underwriting. For the people joining Shepherd, that means the chance to shape both the technology and the business it makes possible. Our backing brings together investors who build technology companies and partners who understand insurance. We are building a company that earns the confidence of both. [app.ashbyhq.com] ANALYTICS ENGINEER THE MISSION: BUILD SHEPHERD’S TRUSTED DATA FOUNDATION As Shepherd grows, more teams, products, and automated systems will depend on data to make decisions. Our challenge is no longer simply getting data into the warehouse. It is turning that data into consistent, trusted representations of Shepherd’s business that can be reused across actuarial, reporting, product workflows, and AI-assisted tools. You will build and own Shepherd’s canonical analytical layer: the shared entities, facts, dimensions, definitions, and business rules that allow those consumers to work from the same foundation. Your work will make it possible for Shepherd to answer important questions consistently, build new analytical products faster, and make AI-assisted analysis more reliable by grounding it in shared business definitions. THE ROLE You will be Shepherd’s first dedicated Analytics Engineer and will report directly to the Data Lead. This is a high-ownership role for someone who can combine dimensional modeling and engineering discipline with the domain discovery and cross-functional collaboration required to establish trusted sources of truth. You will work directly with Actuarial, reporting, operations, engineering, and other data consumers to understand how important business concepts are represented today. You will identify what should be standardized, where legitimate domain differences must remain, and how those decisions should be implemented, tested, documented, and adopted. Building on an existing warehouse, dbt project, and body of analytical work to establish Shepherd’s canonical analytical layer. While working with domain experts across the company, you’ll determine which business concepts to model first and lead their design, implementation, and adoption. This is a data-modeling and platform-ownership role, not an ad hoc analysis or dashboard building position. WHAT YOU’LL DO - Design, build, and own canonical data models for Shepherd’s core business entities and processes. - Partner with domain experts to translate insurance and operational knowledge into explicit facts, dimensions, grains, relationships, and business rules. - Identify what should be shared across Actuarial, reporting, and other consumers while preserving clearly defined domain variants where requirements differ. - Establish the testing, reconciliation, documentation, lineage, ownership, and development practices that make analytical models trustworthy and maintainable. - Evaluate existing models, reports, and actuarial datasets, then lead consumers through migration to reliable, performant shared foundations. - Shape the semantic context that helps people and AI-assisted tools use Shepherd’s data correctly, while keeping models coherent as source systems and platform architecture evolve. - Collaborate with the Data Lead and platform engineers to keep analytical models coherent as source systems and platform architecture evolve. WHO YOU ARE REQUIRED - Strong SQL skills and hands-on experience developing production data models with dbt. - Deep experience with dimensional modeling, including defining model grain, facts, dimensions, historical state, and relationships between business entities. - You have owned important analytical models beyond their initial implementation, including validation, documentation, maintenance, and consumer adoption. - You are comfortable learning an unfamiliar domain directly from subject-matter experts and translating incomplete or conflicting requirements into durable technical designs. - You can lead cross-functional migrations and earn adoption rather than treating model deployment as the end of the work. - You bring sound engineering judgment to analytical systems and value tested, understandable, reusable models over one-off outputs. - You are comfortable operating with ambiguity and taking ownership of a problem whose solution has not already been designed. NICE TO HAVE - Experience in insurance, financial services, or another domain where definitions, historical state, and data quality have material business consequences. - Familiarity with semantic layers, data catalogs, metric definitions, or AI-assisted analytics. - Experience establishing analytics-engineering practices in a growing or relatively early-stage data organization. - Familiarity with Python, Dagster, data ingestion pipelines, and modern software-engineering and CI/CD practices. HOW WE WORK Shepherd runs on four values. Here's what each one means in this seat. - Think big, build big. We exist to protect progress and the industries that rely on it. The work here is aimed at a system that runs on its own, and the roadmap gets sequenced backward from that rather than forward from what's easy. - Win together. We rise as one. We support each other, raise the bar, and celebrate collective success. Come set a standard the rest of the team inherits. - Cross the aisle. Collaboration wins. We listen deeply, work across boundaries, and prioritize shared success over individual lanes. The best product calls here come from engineers who've sat with underwriters and underwriters who understand where the model breaks, and much of this job is listening closely enough on both sides to make that happen. - Go get it. We act with urgency, move with confidence, take smart risks, and push forward with intention. Nobody hands you the roadmap, the data, or the meeting invite. You pull the failing runs, book the time with the underwriters, and decide what matters. BENEFITS 🏥 Premium Healthcare 100% contribution to health, dental, and vision 🥕 Fertility benefits and family building support 🏖️ Flexible PTO Flexibility to take the time off, recharge, and perform 🥗 Daily lunches, dinners, and snacks We work together, and enjoy meals together too 🖥️ SF, NYC, Dallas-Fort Worth, Chicago and LA Offices 📚 Professional Development Access to premium coaching, including leadership development 🏦 Competitive 401(k) Plan 🐶 Dog-friendly office Plenty of dogs to play with and make friends with in the SF office

Requirements

Must-haves

Build the insurance behind the physical world.
Real problems. Real ownership.
The ambition is a platform where experts spend more time on judgment and relationships, supported by software that handles the work around them. Join us to build systems whose decisions help real projects get built.
630+ customers / $500B+ insured project value
Capital to build. Partners to grow with.
$67M total funding / $42M Series B in March 2026
A bigger opportunity ahead
Our backing brings together investors who build technology companies and partners who understand insurance. We are building a company that earns the confidence of both.
THE MISSION: BUILD SHEPHERD’S TRUSTED DATA FOUNDATION
This is a data-modeling and platform-ownership role, not an ad hoc analysis or dashboard building position.
Design, build, and own canonical data models for Shepherd’s core business entities and processes.
Partner with domain experts to translate insurance and operational knowledge into explicit facts, dimensions, grains, relationships, and business rules.
Identify what should be shared across Actuarial, reporting, and other consumers while preserving clearly defined domain variants where requirements differ.
Establish the testing, reconciliation, documentation, lineage, ownership, and development practices that make analytical models trustworthy and maintainable.
Evaluate existing models, reports, and actuarial datasets, then lead consumers through migration to reliable, performant shared foundations.
Shape the semantic context that helps people and AI-assisted tools use Shepherd’s data correctly, while keeping models coherent as source systems and platform architecture evolve.
Collaborate with the Data Lead and platform engineers to keep analytical models coherent as source systems and platform architecture evolve.
Strong SQL skills and hands-on experience developing production data models with dbt.
Deep experience with dimensional modeling, including defining model grain, facts, dimensions, historical state, and relationships between business entities.
You have owned important analytical models beyond their initial implementation, including validation, documentation, maintenance, and consumer adoption.

Nice-to-haves

Experience in insurance, financial services, or another domain where definitions, historical state, and data quality have material business consequences.
Familiarity with semantic layers, data catalogs, metric definitions, or AI-assisted analytics.
Experience establishing analytics-engineering practices in a growing or relatively early-stage data organization.
Familiarity with Python, Dagster, data ingestion pipelines, and modern software-engineering and CI/CD practices.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aiapisqlpythonci/cdrestgo

Platform: ashby
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Pto

Professional Development