Director, Revenue Operations - Strategy & Planning

ClickHouse ClickHouse · Data AI · United States · Go-To-Market

Director of Revenue Operations focusing on Strategy & Planning for a cloud analytics company that supports AI workloads and customers. The role involves GTM architecture, planning, pipeline modeling, capacity and quota planning, and comp design. Requires strong analytical and modeling skills, SQL fluency, and familiarity with modern analytics stacks. The company is a leader in real-time analytics, data warehousing, observability, and AI workloads.

What you'd actually do

  1. Own GTM architecture: markets, segments, roles, coverage model, and the planning logic that turns business strategy into a deployable revenue system.
  2. Lead annual planning end-to-end: capacity modeling, territory design, quota allocation, and the headcount and expense plan that funds it.
  3. Design the operating cadence with sales leadership: forecast roll-ups, pipeline reviews, QBR and MBR support, and the analytical work that drives decisions inside those forums.
  4. Partner with FP&A on controllership: headcount and expense management, comp plan modeling, forecast accuracy, and variance analysis.
  5. Build the experimentation and measurement frameworks that turn GTM system outputs into the next version of the system: what is working, what is not, and what to change.

Skills

Required

  • Revenue operations
  • Sales strategy
  • GTM finance
  • Strategy consulting
  • Team leadership
  • Owner-operator mindset
  • Data analysis
  • Modeling
  • SQL
  • ClickHouse
  • dbt
  • Notebook environment
  • Version-controlled analytical code
  • Repeatable pipelines

Nice to have

  • Python
  • Consumption-based or usage-based business models
  • MBA or equivalent post-graduate education

What the JD emphasized

  • 10+ years in revenue operations, sales strategy, GTM finance, or strategy consulting, with at least five years leading a team.
  • SQL fluency required
  • Hands-on familiarity with ClickHouse, dbt, or a comparable modern analytics stack expected.
  • Comfort building in a notebook environment, working with version-controlled analytical code, and shipping repeatable pipelines rather than one-off spreadsheets.