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Staff Analytics Engineer, GTM

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Posted within 60 days ·

  • hybrid
  • FullTime
  • Data
  • San Francisco
Work arrangement
hybrid
Employment
FullTime
Stated compensation
USD 200,000–250,000 1 YEAR
Stated sponsorship
Not stated
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Remote policy
hybrid
“Provider workplace type: hybrid”
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Minimum experience (years)
8
“Have 8+ years of experience in analytics engineering, data engineering, or analytics, with significant time spent on Sales, Marketing, or Finance data at a SaaS company”
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Employment type
FullTime
Compensation
USD 200,000–250,000 1 YEAR
7 fields not stated in this posting
Employer sponsorship
Not specified
Geographic scope
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Degree requirement
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Original job description

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About Scribe Scribe is where exceptional people come to do the best work of their careers. More than 94% of the Fortune 500 use Scribe to own their specialized intelligence: the unique way their teams work, decide, and get things done. Our Specialized Intelligence platform automatically captures how work happens and turns it into a living asset for people and AI agents. We're growing fast. Since our founding in 2019, we've reached 7 million users across 600,000 businesses. Based in San Francisco, we're a LinkedIn Top Startup, valued at over $1B, and backed by leading investors. Join us in our mission to transform how people work.
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tl;dr – Why this role matters At Scribe, data is the foundation of how we make decisions — we take it very seriously. As we accelerate our sales organization into a first-class enterprise team, the data behind our go-to-market motion needs to be just as strong as the data behind our product. We’re looking for a hands-on builder to lay the foundation of GTM data at Scribe — designing first-principles data models across Sales, Marketing, and Finance, and building a culture where every GTM decision starts from a trusted, shared source of truth. Hiring Manager: Melanie Herscher, Head of Data About the role As the Lead Analytics Engineer for GTM, you’ll be the first dedicated data hire for our go-to-market organization, reporting directly to the Head of Data. You’ll design and build the core data models that define how Scribe measures pipeline, bookings, revenue, and customer growth, and you’ll set the standards that future GTM analytics work is built on. As the team grows, you’ll have the opportunity to mentor and shape the analysts and analytics engineers who join it. Working hand in hand with sales, marketing, finance, and RevOps, you will answer Scribe’s most critical go-to-market questions and turn them into durable, self-serve data products. Your work will be central to how we scale our enterprise motion, helping leadership understand what drives pipeline and revenue, and where to invest next. Key responsibilities of this role include: Build Scribe’s foundational GTM data models from first principles, starting with Sales and extending across Marketing and Finance, so that metrics like pipeline, bookings, ARR, and conversion have one clear, consistent definition. Turn ambiguous business questions into simple, actionable metrics, partnering directly with GTM and finance leaders to define the KPIs, dashboards, and analyses they run the business on. Be a cross-functional magnet with our sales, marketing, and finance teams, establishing trusted partnerships and serving as the go-to resource for GTM data questions, deep-dive analysis, and technical guidance. Lay the foundation of GTM data culture through reproducible work, documentation, data quality standards, and self-serve tooling that make data accessible to everyone in the GTM org. Mentor and help grow the team as GTM analytics scales, setting the technical bar and best practices for the analysts and analytics engineers who follow. What makes you a great fit You’d be a great fit for this role if this sounds like you: Have 8+ years of experience in analytics engineering, data engineering, or analytics, with significant time spent on Sales, Marketing, or Finance data at a SaaS company Have built data models from the ground up, and know how to design for clarity, scale, and trust rather than inheriting what already exists Strong technical proficiency in our tech stack – Snowflake, dbt cloud, Sigma, Mixpanel, and Looker – with expert SQL and data modeling skills Fluent in GTM and revenue data, including CRM, marketing, and billing systems, and concepts like pipeline, bookings, ACV/ARR, funnel conversion, and attribution Customer mindset, adept at understanding how sellers, marketers, and finance partners actually work, and communicating complex findings clearly to non-technical audiences Low ego. You care about building things and recognize that this may require rolling your sleeves up, getting in the trenches, and owning everything from data modeling to ad-hoc analysis Proactive, high-output orientation. You push insights and data onto teams rather than waiting for requests to emerge from them Outcomes over output. You thrive on creating business value and know when to build a durable model v/s doing ugly napkin math to bias towards action Experience building technical and semantic infrastructure to power internal natural language agents and agentic automation Bonus Points Experience working in high-paced Enterprise SaaS startups, especially during a shift from self-serve to enterprise sales Experience mentoring analysts or analytics engineers, or serving as a tech lead on a data team Experience creating a step-function change in a GTM team’s effectiveness with the help of AI tooling Benefits Healthcare Coverage – Comprehensive health, dental, and vision plans, including two $0/month medical plan options for employees Equity – Ownership in what we're building 401(k) Plan – through Vestwell Flex Benefit – $500/year for home office equipment, productivity tools, learning & development or fitness/wellness Commuter Benefits – $100/month for SF based employees PTO – Flexible paid time off and company holidays Parental Leave – Paid leave to support growing families Wellness & Family Support – Free Talkspace membership, One Medical access (location-dependent), and Kindbody discounts for family planning At Scribe, we celebrate our differences and are committed to creating a workplace where all employees feel supported and empowered to do their best work. Scribe is proud to be an Equal Opportunity Employer. Our Worker Privacy notice can be found here.
Original formatting and links

About Scribe

Scribe is where exceptional people come to do the best work of their careers. More than 94% of the Fortune 500 use Scribe to own their specialized intelligence: the unique way their teams work, decide, and get things done. Our Specialized Intelligence platform automatically captures how work happens and turns it into a living asset for people and AI agents.

We're growing fast. Since our founding in 2019, we've reached 7 million users across 600,000 businesses. Based in San Francisco, we're a LinkedIn Top Startup, valued at over $1B, and backed by leading investors. Join us in our mission to transform how people work.

tl;dr – Why this role matters

At Scribe, data is the foundation of how we make decisions — we take it very seriously. As we accelerate our sales organization into a first-class enterprise team, the data behind our go-to-market motion needs to be just as strong as the data behind our product. We’re looking for a hands-on builder to lay the foundation of GTM data at Scribe — designing first-principles data models across Sales, Marketing, and Finance, and building a culture where every GTM decision starts from a trusted, shared source of truth.

Hiring Manager: Melanie Herscher, Head of Data

About the role

As the Lead Analytics Engineer for GTM, you’ll be the first dedicated data hire for our go-to-market organization, reporting directly to the Head of Data. You’ll design and build the core data models that define how Scribe measures pipeline, bookings, revenue, and customer growth, and you’ll set the standards that future GTM analytics work is built on. As the team grows, you’ll have the opportunity to mentor and shape the analysts and analytics engineers who join it.

Working hand in hand with sales, marketing, finance, and RevOps, you will answer Scribe’s most critical go-to-market questions and turn them into durable, self-serve data products. Your work will be central to how we scale our enterprise motion, helping leadership understand what drives pipeline and revenue, and where to invest next.

Key responsibilities of this role include:

  • Build Scribe’s foundational GTM data models from first principles, starting with Sales and extending across Marketing and Finance, so that metrics like pipeline, bookings, ARR, and conversion have one clear, consistent definition.

  • Turn ambiguous business questions into simple, actionable metrics, partnering directly with GTM and finance leaders to define the KPIs, dashboards, and analyses they run the business on.

  • Be a cross-functional magnet with our sales, marketing, and finance teams, establishing trusted partnerships and serving as the go-to resource for GTM data questions, deep-dive analysis, and technical guidance.

  • Lay the foundation of GTM data culture through reproducible work, documentation, data quality standards, and self-serve tooling that make data accessible to everyone in the GTM org.

  • Mentor and help grow the team as GTM analytics scales, setting the technical bar and best practices for the analysts and analytics engineers who follow.

What makes you a great fit

You’d be a great fit for this role if this sounds like you:

  • Have 8+ years of experience in analytics engineering, data engineering, or analytics, with significant time spent on Sales, Marketing, or Finance data at a SaaS company

  • Have built data models from the ground up, and know how to design for clarity, scale, and trust rather than inheriting what already exists

  • Strong technical proficiency in our tech stack – Snowflake, dbt cloud, Sigma, Mixpanel, and Looker – with expert SQL and data modeling skills

  • Fluent in GTM and revenue data, including CRM, marketing, and billing systems, and concepts like pipeline, bookings, ACV/ARR, funnel conversion, and attribution

  • Customer mindset, adept at understanding how sellers, marketers, and finance partners actually work, and communicating complex findings clearly to non-technical audiences

  • Low ego. You care about building things and recognize that this may require rolling your sleeves up, getting in the trenches, and owning everything from data modeling to ad-hoc analysis

  • Proactive, high-output orientation. You push insights and data onto teams rather than waiting for requests to emerge from them

  • Outcomes over output. You thrive on creating business value and know when to build a durable model v/s doing ugly napkin math to bias towards action

  • Experience building technical and semantic infrastructure to power internal natural language agents and agentic automation

Bonus Points

  • Experience working in high-paced Enterprise SaaS startups, especially during a shift from self-serve to enterprise sales

  • Experience mentoring analysts or analytics engineers, or serving as a tech lead on a data team

  • Experience creating a step-function change in a GTM team’s effectiveness with the help of AI tooling

Benefits

  • Healthcare Coverage – Comprehensive health, dental, and vision plans, including two $0/month medical plan options for employees

  • Equity – Ownership in what we're building

  • 401(k) Plan – through Vestwell

  • Flex Benefit – $500/year for home office equipment, productivity tools, learning & development or fitness/wellness

  • Commuter Benefits – $100/month for SF based employees

  • PTO – Flexible paid time off and company holidays

  • Parental Leave – Paid leave to support growing families

  • Wellness & Family Support – Free Talkspace membership, One Medical access (location-dependent), and Kindbody discounts for family planning

At Scribe, we celebrate our differences and are committed to creating a workplace where all employees feel supported and empowered to do their best work. Scribe is proud to be an Equal Opportunity Employer.

Our Worker Privacy notice can be found here.

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