Staff Analytics Engineer

Role overview

This Staff Analytics Engineer role focuses on owning and unifying the go-to-market data model that powers revenue decisions across a fast-scaling AI platform serving plaintiff law firms. The position sits on a central data team reporting to the Head of Data Engineering, where data is treated as a first-class function and the business is doubling rapidly. The mission is to eliminate conflicting metric definitions across teams and build the trusted, certified data foundation that both human analysts and AI systems rely on.

Responsibilities

- Partner with analysts and stakeholders across Sales, Marketing, Customer Success, and RevOps to build and maintain GTM models covering pipeline, funnel, campaigns, and revenue, sourced from CRM and marketing automation systems into the warehouse and semantic layer - Design semantic models for core SaaS metrics including pipeline coverage, funnel conversion, CAC, win rate, sales cycle time, ARR, and bookings - Define and own the metrics certification framework and catalog, deciding what qualifies as a governed definition and arbitrating conflicts when teams define the same thing differently - Establish modeling standards, testing patterns, and semantic layer conventions that other analytics engineers and contributing analysts build inside - Instrument models against the team's alerting so failures and drift surface before stakeholders notice, and maintain documentation for owned models and definitions - Mentor analytics engineers, set the technical bar, and stand up AI-grounded internal tools that let stakeholders get trustworthy answers without filing tickets

Requirements

- 8+ years in analytics engineering, including time at a staff or senior IC level setting technical direction others followed - Deep dbt expertise (advanced modeling patterns, macros, packages, testing) plus SCD-type tables from multiple sources, alongside strong SQL and transformation skills - Expert command of a modern stack including Snowflake, dbt, and a semantic or BI layer such as Omni or Hex - Experience designing semantic models or metric layers for both human and AI consumption - Hands-on experience modeling GTM systems built on HubSpot, Salesforce, or comparable CRM and marketing automation platforms - Track record resolving cross-team "the numbers don't match" disputes and unifying everyone behind a single definition - Proficiency with AI-assisted development (e.g., agentic pipelines, skill-based workflows, MCP-style integrations) - Strong communication, mentoring instincts, and comfort building where the playbook does not yet exist

Nice to have

- Experience in a regulated or high-sensitivity data environment (legal, healthcare, or financial services) - Experience enabling analysts outside the core team to contribute production models - B2B SaaS background, especially selling to small and mid-sized businesses or professional services firms

Benefits and work setup

- US salary range: $225,000–$305,000 - Competitive salary and equity, plus a 401(k) with employer matching - Health, dental, vision, and life insurance, with short- and long-term disability coverage - Commuter benefits and in-office perks for on-site employees - Autonomous work environment with workplace setup reimbursement and a telecomm stipend - Flexible time off plus holidays, with quarterly team gatherings