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Salary: USD 280,000 - 350,000 / annual
ClickHouse is a fast-growing analytics and data platform company (Forbes Cloud 100 2025, $400M Series D) with 4,000+ customers and 250%+ YoY ARR growth. You'll own a hybrid enterprise territory covering both new account acquisition and expansion within existing customers.
In this role, you'll manage the full commercial lifecycle: initial prospecting through technical evaluation, security review, procurement, and close. You'll work closely with Solutions Architects on technical wins while owning commercial strategy and deal closure. Your responsibilities include building pipeline, identifying expansion opportunities across teams and use cases, managing renewals and consumption commitments, and multi-threading across data platform teams, budget owners, security, and executive sponsors.
You'll handle complex enterprise sales cycles involving security questionnaires, legal redlines, vendor onboarding, and potentially BYOC or private-deployment requirements. You'll develop business cases (TCO analysis, migration plans, risk mitigation) for champions and maintain accurate Salesforce forecasting for leadership planning.
ClickHouse sells to technical buyers—data platform teams, architects, and engineering leaders—so you'll spend significant time on technical evaluations and architectural discussions. You'll also participate in developer community activities (meetups, conferences, events) in your territory.
Required: 6+ years selling technical infrastructure (databases, data platforms, cloud, observability, developer tools) to enterprise buyers. You need a track record closing complex deals through security, legal, and procurement; enough technical fluency to discuss architecture (e.g., why workloads move from Elasticsearch); experience with hybrid quotas (new business + expansion + renewal); familiarity with consumption-based or usage-metered commercial models; and ability to orchestrate cross-functional teams. Experience with developer-led and bottom-up adoption, AI-native companies, and accurate forecasting (including bad numbers) are essential.
