Head of Revenue Operations

The Head of Revenue Operations will shape and scale the revenue engine of a global B2B SaaS business operating across multiple brands and go-to-market models. This strategic leadership role combines product-led growth, sales-assisted acquisition, and an expanding enterprise AI motion into a unified, data-driven operating model. You will partner with Sales, Customer Success, Marketing, Finance, and Data teams to optimize the customer journey from initial engagement through renewal. The role offers the opportunity to build and develop critical capabilities across deal desk operations, field enablement, revenue automation, and business analysis. You will use data and applied AI to improve forecasting, increase sales productivity, and eliminate unnecessary manual work. Success means creating scalable processes, trusted performance insights, and a more efficient revenue organization in a distributed, multi-brand environment.

The ideal candidate is a strategic and technically capable revenue operations leader with a strong background in B2B SaaS, go-to-market transformation, and scaling operational functions. They should be comfortable building teams and processes from the ground up, using data to guide decisions, and leading change across a globally distributed organization. Required qualifications include:

• At least 10 years of experience in Revenue Operations or Go-to-Market Operations, including at least five years leading the function at a B2B SaaS company with approximately $30 million to $150 million in annual recurring revenue.
• Demonstrated experience supporting both product-led and sales-assisted go-to-market models, with an understanding of their different operational requirements, customer journeys, and performance metrics.
• Deep expertise in Salesforce and the broader revenue technology ecosystem, including forecasting, quote-to-cash processes, marketing automation, business intelligence, and billing systems.
• Strong technical understanding of data, including data modeling, system architecture, and the ability to collaborate effectively with data engineering teams.
• Practical experience deploying AI and automation within a go-to-market organization, with the ability to evaluate real operational impact rather than relying solely on demonstrations or theoretical use cases.
• Proven ability to build and scale operational functions, establish repeatable processes, and recruit high-performing teams and leaders.
• Experience designing forecasting frameworks, pipeline management processes, territory and coverage models, quota structures, and incentive plans.
• Strong analytical and commercial judgment, with the ability to interpret complex business performance data and translate findings into clear recommendations and measurable actions.
• Experience building or managing deal desk operations, enterprise sales processes, and cross-functional deal review workflows is highly valuable.
• Ability to design and implement scalable customer lifecycle and renewal processes, including technology-enabled approaches that improve efficiency.
• Strong stakeholder management and communication skills, with the ability to align Sales, Customer Success, Marketing, Finance, Product, Engineering, and Data teams around shared goals.
• Comfort operating in a globally distributed, multi-brand business where standardization requires collaboration, prioritization, and sound judgment.
• Ability to balance strategic planning with hands-on execution, establish clear ownership, and measure progress against operational and revenue performance indicators.