Senior Finance Manager, GTM
About Us
Temporal is an open source programming model designed to simplify code, enhance application reliability, and support developers in delivering features faster. Our mission is to serve as the foundational tool for every developer's toolkit and we are assembling the team that will realize this vision. Our core values guide our actions, emphasizing curiosity, drive, collaboration, genuineness, and humility. Temporal is expanding and we seek individuals who share our values, challenge conventional wisdom, and wish to shape our future. If you are passionate about improving the developer experience, contributing to open-source software, and joining our dynamic team, we would love to hear from you.
What You’ll Do
Own the end-to-end revenue forecast for consumption-based products, including short-term and long-range views.
Build and maintain bottoms-up forecasting models that incorporate usage drivers, customer cohorts, ramp curves, contract structures, and expansion behavior.
Partner closely with Data Science to align financial forecasts with statistical consumption models, usage signals, and predictive analytics.
Continuously refine forecasts based on actuals, usage trends, pipeline changes, and GTM performance.
Develop and maintain highly detailed financial models in Google Sheets and Excel.
Translate outputs from data science models into clear financial assumptions, scenarios, and executive-ready forecasts.
Perform scenario analysis, sensitivity analysis, and stress-testing to inform pricing, packaging, and GTM strategy.
Translate ambiguous or incomplete data into structured assumptions and clearly documented models.
Partner Closely With GTM, RevOps, and Data
Support forecasting for new GTM motions, pricing changes, and product launches.
Lead headcount and tooling investment planning, partnering with functional leaders to translate growth plans into hiring roadmaps, tooling needs, and expense forecasts.
Operate Effectively in a Hypergrowth Environment
Support a business that is scaling rapidly, where historical data is imperfect and judgment matters.
Help design forecasting processes that combine data-driven rigor with financial intuition and can scale over time.
Prepare materials and insights for QBRs, executive reviews, and board discussions, with a focus on revenue predictability, risk, and forecast confidence.
Cross-Functional Financial Leadership
Partner with Accounting on revenue recognition considerations and variance analysis tied to usage-based billing.
Support annual planning, rolling forecasts, and budget updates with a heavy emphasis on revenue accuracy.
Proactively identify risks and opportunities in the revenue model and communicate them clearly to leadership.
Background & Experience
6-10 years of relevant experience, with early career training in one or more of the following: Investment Banking, Private Equity or Venture Capital, Revenue-focused FP&A, or Strategic Finance at a high-growth technology company.
Direct experience forecasting consumption-based or usage-driven revenue is strongly preferred.
Experience operating in a hypergrowth environment (rapid customer growth, evolving GTM motion, limited historical data).
Expert-level Excel and Google Sheets skills; must be able to independently build complex, multi-layered financial models.
Strong understanding of revenue forecasting mechanics, cohort analysis, ramp modeling, and expansion dynamics.
Comfort partnering closely with Data Science and Analytics teams, translating model outputs into financial forecasts and decisions.
Ability to evaluate model performance, understand drivers of forecast error, and iterate assumptions accordingly.
Highly iterative and action-oriented; comfortable revising forecasts frequently as new information becomes available.
Strong judgment under uncertainty; able to make and defend assumptions when data is incomplete or signals conflict.
Direct, clear communicator who can explain complex financial concepts to non-finance stakeholders.
High ownership mentality with a bias toward accountability and results.
Nice to Have
Experience with SaaS and cloud metrics (NDR, usage efficiency, margin by product, CAC payback, LTV).
Familiarity with tools such as NetSuite, Salesforce, Snowflake, or modern BI platforms.
Prior experience working closely with Data Science teams on forecasting or predictive modeling.
MBA or CFA is preferred, but not required.