Commercial Account Executive

Recognized on the 2025 Forbes Cloud 100 list, Click House is one of the most innovative and fast-growing private cloud companies. With more than 3,000 customers and ARR that has grown over 250 percent year over year, Click House leads the market in real‑time analytics, data warehousing, observability, and AI workloads.

The company’s sustained, accelerating momentum was recently validated by a $400M Series D financing round. Over the past three months, customers including Capital One, Lovable, Decagon, Polymarket, and Airwallex have adopted the platform or expanded existing deployments. These customers join an established base of AI innovators and global brands such as Meta, Cursor, Sony, and Tesla.

We’re on a mission to transform how companies use data. Come be a part of our journey!

Our commercial segment — companies with up to 250 employees — is predominantly developer‑ and engineer‑led. These buyers don’t respond to decks and discovery scripts. They respond to someone who speaks their language, understands their architecture, and can help them think through a real problem. That’s who we’re hiring.

As a Commercial Account Executive at Click House, you’ll own the full sales cycle for inbound, product‑led, and self‑serve accounts in this segment. You’ll engage with data engineers, platform teams, and technical founders when they’re evaluating Click House for a real use case — and your job is to help them succeed faster. The best deals in this segment don’t feel like sales;

they feel like an engineering consultation that ends in a contract.

• Own the full sales cycle from inbound lead to close for accounts in the sub‑250 employee segment, with a focus on speed, technical depth, and conversion quality.
• Engage directly with data engineers, platform architects, and technical founders to understand their use cases, data volumes, query patterns, and infrastructure requirements — and map those to Click House capabilities.
• Troubleshoot schema design questions, ingestion patterns, and integration challenges during the evaluation process; serve as a trusted technical advisor rather than a traditional sales rep.
• Identify expansion opportunities within the existing self‑serve and product‑led customer base; convert usage signals into meaningful commercial relationships.
• Partner with Solutions Engineers on more complex evaluations, and advocate for customer needs internally with Product and Engineering.
• Maintain rigorous pipeline hygiene — documenting technical context, decision criteria, stakeholders, and next steps in Salesforce so nothing falls through the cracks.
• Contribute to playbooks, technical objection‑handling guides, and onboarding materials that help the team scale what’s working.
• Participate in developer community events, technical meetups, and online forums where our users naturally gather.

• A technical foundation that earns respect in engineering conversations — built through experience as a data engineer, solutions engineer/architect, software engineer, or similar role.
• Comfort with the modern data stack: columnar databases, streaming ingestion (Kafka, Kinesis), cloud infrastructure, and SQL‑heavy analytics workflows. Hands‑on experience with Click House, DuckDB, Druid, Pinot, Big Query, Snowflake, or similar is a strong plus.
• Some customer‑facing experience — whether in pre‑sales, technical account management, solutions engineering, or a customer‑success capacity. You’ve navigated technical conversations with real stakes before.
• An instinct for moving quickly. This segment runs on short cycles. You know how to drive urgency without being pushy, and how to remove technical blockers that stall deals.
• Strong written and verbal communication. You can simplify complex concepts without dumbing them down, and you write clearly enough that your emails actually get responses from engineers.
• Curiosity about the business side of technology. You’re interested in understanding why companies buy, not just what they’re building.
• Ownership mentality. You’re comfortable operating with autonomy, making judgment calls without a playbook, and learning from what doesn’t work.