Gitbook

Growth & Data (IC)

2mo ago
WorldwideRemote
Gitbook

Growth & Data (IC)

2mo ago
WorldwideRemoteuser researchdata analysisexperimentationdata modelingdata pipelinesdashboarding

Data-driven role focused on driving product and business growth through experimentation, data analysis, and user research.

About the company

  • We’re building the best platform for authoring, publishing, and maintaining world-class docs. Close to 40,000 sign-ups per month , over 1 00k Monthly Active Users , used by 2M+ people and thousands of teams like Zoom, FedEx, Nvidia, Snyk, and Google. We’re profitable , backed by P9 Capital, Notion Capital, and Fly VC, and our amazing team is spread across 15 countries in North America, Europe, and Asia.

About the product

  • You think in terms of problems and outcomes , not just queries or models. You’re comfortable talking to stakeholders, pushing back, and making trade-offs.

Conditions

  • You’ll be one of the few people at GitBook owning data as a product and a lever for growth .
  • This is a role where:
  • your work directly shapes decisions
  • your scope is wide
  • and your impact is visible
  • 👥 Join GitBook at a pivotal time as we evolve our product and team. This is a chance to shape our product, craft, and culture .

How to apply

  • We aim to keep things simple and relevant:
  • Intro call (fit & expectations)
  • Deep dive with the hiring manager (Head of Data)
  • Practical discussion / case
  • Final conversation with the team

Other

  • This is not a traditional data role.
  • You won’t just build dashboards. You won’t just maintain pipelines. You’ll own problems end-to-end , using data to drive product and business impact.
  • Run user research (interviews, feedback loops, data analysis) and translate feedback into insights that allow for actionable growth opportunities
  • Work directly with stakeholders to frame problems, challenge assumptions, and prioritize what matters
  • Design and run experiments, analyses, and campaigns to drive growth and product adoption
  • Build lightweight data applications or workflows to enable faster decision-making
  • Continuously improve how we structure and expose data across the company, be highly involved with our data modeling layer
  • Connect tools and systems (product, marketing, sales) into a coherent data ecosystem
  • Push the team toward clarity and simplicity in how we measure and reason about the business
  • You’ll operate across commercial and product functions— with a strong bias toward action and impact .
  • Important to note is that this is a foundational role.
  • Our stack today:
  • GCP (BigQuery, Composer)
  • dbt (Cloud / via Cursor)
  • Replit (data apps & internal tooling)
  • Tableau / Count (analysis & exploration)
  • Amplitude, Segment (product & event data)
  • We don’t expect you to know everything, but you should be comfortable owning and evolving a modern data stack .
  • You can go from:
  • messy question → structured problem
  • raw data → usable model
  • insight → shipped action
  • You don’t get stuck in one layer.
  • You know when to:
  • build vs hack
  • go deep vs move fast
  • say no vs explore
  • You optimize for impact, not perfection .
  • You’re strong in:
  • SQL and data modeling
  • working with modern data stacks
  • navigating data pipelines and systems
  • You don’t need to be a pure data engineer — but you’re not afraid of technical complexity.
  • You enjoy:
  • managing diverse stakeholders
  • bringing alignment
  • translating challenges to growth promoting solutions
  • Not a reporting role focused on dashboards
  • Not a pure data engineering role
  • Not a traditional analyst role doing long, static analyses
  • You have experience with:
  • a high growth start up environment, especially PLG
  • working as or close to an analytics engineer / data generalist
  • working in a product, marketing or growth-focused data role
  • You enjoy:
  • ambiguity
  • ownership
  • figuring things out from first principles
  • talk to customers
  • You’ve felt frustrated being:
  • too far from business decisions
  • stuck maintaining dashboards
  • or limited to one layer of the stack