Senior Analytics Engineer

Solv is a company dedicated to transforming healthcare by making it accessible and effortless for all. They are seeking a Senior Analytics Engineer to own their analytics stack, ensuring the data pipeline is efficient and accurate while also shaping customer-facing analytics and evolving AI-powered analytics capabilities.

Responsibilities:

• Own the dbt models that power Solv’s critical metrics across both internal and customer-facing surfaces. This includes table architecture, field logic, metric definitions, and the modeling choices that determine whether our pipeline meets its SLAs as we constantly add complexity with new products and initiatives
• Set and enforce modeling standards — naming conventions, testing patterns, schema design, documentation. When a metric doesn’t exist or a definition is ambiguous, you define it, build it, and get buy-in
• Diagnose and resolve data issues by tracing lineage across source systems and coordinating with engineering when upstream changes break downstream models
• Own the embedded dashboards and reporting that partners interact with daily inside Solv’s product. Design, build, and iterate on how customers see and use their data
• Manage the full cycle of customer analytics requests: triage what’s a quick fix, what’s a modeling change, and what’s a product gap that needs a different solution
• Design automated analytics deliveries — scheduled reports, data exports, and insight summaries — that reach partners without them needing to log in
• Help evolve our early-stage AI analytics capabilities from internal tools into something that can scale — and eventually reach customers directly in-product
• Build evaluation frameworks and quality guardrails for AI-generated analytics. The bar is higher when output reaches customers — define what 'trustworthy enough to ship' looks like
• Keep a pulse on how AI is changing analytics delivery. The tools and approaches are shifting fast; we need someone who evaluates new capabilities with a critical eye, makes smart tradeoff recommendations, and isn’t wedded to one approach just because it’s familiar

Requirements:

• 5+ years owning an analytics stack end-to-end — from raw data to trusted models to the tools non-technical teams depend on
• Strong data modeling judgment
• Genuinely curious about the business
• Communicate clearly across audiences
• Enjoy working on a small, cross-functional team where your work directly shapes how the company and its customers make decisions
• Strong SQL and data transformation framework experience (e.g. dbt)
• Experience building and maintaining dashboards and semantic modeling layers in BI platforms (e.g. Looker/LookML)
• Experience writing and optimizing models with cloud data warehouses (e.g. Redshift, Snowflake)
• Familiarity with ETL pipeline tools (e.g. Fivetran, Airbyte)
• Experience with AI-powered development tools and automated insight generation (e.g. Claude Code)