Senior Analytics Engineer

Role overview

This role owns the bridge between a centralized data platform and the business, transforming raw warehouse data into trusted, well-modeled datasets and reliable dashboards. The position blends analytics engineering craft (dimensional modeling, semantic layers, metric governance) with hands-on BI delivery in a regulated, multi-tenant environment. It's suited to a senior individual contributor who treats modeling discipline as the foundation and trustworthy reporting as the payoff.

Responsibilities

- Design and maintain dbt models across staging, intermediate, and mart layers, including incremental logic, tests, and documentation - Apply dimensional modeling techniques such as star schemas and slowly-changing dimensions to keep datasets correct, performant, and reusable - Define and govern core business metrics so a single, consistent definition appears across every report and dashboard - Build and maintain the semantic layer between marts and BI, partnering with stakeholders to reconcile competing metric definitions into one source of truth - Develop dashboards and reports in the BI layer (Omni) grounded in modeled data, with attention to row-level security, performance, and access controls - Investigate anomalies end-to-end, tracing issues from the dashboard through BI, models, and pipelines back to root cause - Establish conventions, raise the quality bar, and bring durable structure to a growing analytics engineering practice

Requirements

- Senior-level experience as an analytics engineer or equivalent role with strong engineering rigor - Deep, hands-on expertise with dbt for modeling, testing, documentation, and incremental builds - Solid grasp of dimensional modeling, grain discipline, and slowly-changing dimensions - Experience building dashboards in a modern BI tool and translating ambiguous business questions into clear, usable reporting - Comfort operating in a regulated, multi-tenant environment with sensitive data - Ability to move fast, iterate frequently, and bring order to inherited data assets as comfortably as building new ones

Nice to have

- Background in a regulated industry (healthcare, insurance, benefits, or financial services), including handling sensitive or PHI data - Experience with a dedicated semantic or metrics layer, such as the dbt Semantic Layer or comparable tooling - Familiarity with decision-support or analytical workloads, including statistical concepts in support of data-driven products - Prior experience as an early or first dedicated analytics engineer, setting durable patterns on a growing team - Experience mentoring other analytics engineers or analysts and setting technical standards

Benefits and work setup

- Remote position - Listed salary range of $155,000–$175,000, with final placement depending on skills, experience, qualifications, and internal equity - Comprehensive benefits package offered alongside base compensation; full details reviewed during the interview process