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.
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.