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Scribe

AI-powered SaaS generates step-by-step guides

Lead Analytics Engineer - GTM

Data EngineeringConfirmed live in the last 24 hours
Full-timeSan Francisco, CA, USAHybrid

About the Job

Requirements

  • Have 8+ years of experience in analytics engineering, data engineering, or analytics, with significant experience working with Sales, Marketing, or Finance data at a SaaS company.
  • Have built data models from the ground up and be able to design them for clarity, scale, and trust.
  • Have strong technical proficiency with Snowflake, dbt Cloud, Sigma, Mixpanel, Looker, SQL, and data modeling.
  • Be fluent in go-to-market and revenue data, including CRM, marketing, and billing systems, and concepts such as pipeline, bookings, ACV/ARR, funnel conversion, and attribution.
  • Understand how sellers, marketers, and finance partners work, and communicate complex findings clearly to non-technical audiences.
  • Be willing to take hands-on ownership across data modeling and ad hoc analysis.
  • Proactively push insights and data to teams rather than waiting for requests.
  • Be able to prioritize business outcomes and choose between durable models and quick analyses when appropriate.
  • Have experience building technical and semantic infrastructure to power internal natural language agents and agentic automation.

Responsibilities

  • Build foundational go-to-market data models from first principles, starting with Sales and extending across Marketing and Finance, so that metrics such as pipeline, bookings, ARR, and conversion have clear, consistent definitions.
  • Translate ambiguous business questions into actionable metrics, partnering with go-to-market and finance leaders to define the KPIs, dashboards, and analyses they use to run the business.
  • Partner with Sales, Marketing, and Finance teams, serving as a resource for go-to-market data questions, deep-dive analysis, and technical guidance.
  • Establish reproducible work, documentation, data quality standards, and self-serve tooling that make data accessible across the go-to-market organization.
  • Mentor and help grow the team as go-to-market analytics scales, setting technical standards and best practices for future analysts and analytics engineers.

Desired Qualifications

  • Experience working at a fast-paced enterprise SaaS startup, especially during a shift from self-serve to enterprise sales.
  • Experience mentoring analysts or analytics engineers, or serving as a technical lead on a data team.
  • Experience creating a substantial improvement in a go-to-market team's effectiveness using AI tools.

About the Company

Scribe

AI-powered SaaS generates step-by-step guides

ScribeHow provides an AI-powered platform for creating step-by-step how-to guides and training documents as a SaaS service. It automatically generates guides for web or desktop processes, reducing manual documentation effort and saving time for onboarding, SOPs, and training materials. The platform also auto-redacts sensitive information from screenshots to support data privacy compliance. The freemium model lets users start for free and upgrade for access to more features, appealing to both small businesses and large enterprises. ScribeHow differentiates itself through its AI-generated, scalable documentation workflow and built-in redaction for compliance, making it easier for teams to grow and standardize processes. The company's goal is to simplify and scale the creation of instructional content across organizations of all sizes.

Company size
201-500
Company stage
Series C
Total funding
$130M
Headquarters
San Francisco, CA
Founded
2019

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