Shepherd
Analytics Engineer
$165K–$185K
San Francisco · On-site · Full-time · Posted Oct 7, 2026
About the job
Build and own Shepherd’s canonical analytical data layer, translating business and insurance concepts into trusted, reusable models for actuarial, reporting, operational, and AI-assisted use.
What you'll do
- Design and maintain canonical models for core business entities and processes, including their facts, dimensions, relationships, and business rules.
- Establish testing, reconciliation, documentation, lineage, and ownership practices, and lead consumers through migration to shared models.
- Collaborate with domain experts, data consumers, and platform engineers to define and adopt reliable analytical foundations.
What they ask for
- Strong SQL skills and hands-on experience developing production data models with dbt.
- Deep experience with dimensional modeling, including model grain, facts, dimensions, historical state, and entity relationships.
- Experience owning important analytical models through validation, documentation, maintenance, and consumer adoption.
- Ability to translate incomplete or conflicting requirements into durable technical designs and lead cross-functional migrations.
Nice to have
- Experience in insurance, financial services, or another consequential data domain; familiarity with semantic layers, data catalogs, metric definitions, or AI-assisted analytics.
- Familiarity with Python, Dagster, data ingestion pipelines, and modern software-engineering and CI/CD practices.
Pay
$165K – $185K (base salary)
Tools
SQL, dbt, Python, Dagster
AI focus
Shape shared business definitions and semantic context so AI-assisted tools can use Shepherd’s data correctly and make analysis more reliable.
Model-written summary · the original posting is authoritative