Dremio, the Agentic Lakehouse Company, announced that Matt Quarfoot has been appointed Chief Revenue Officer. Quarfoot brings over 20 years of enterprise sales leadership experience across cloud-native and data infrastructure companies. He succeeds Jeff McAllister, who is retiring after a strong tenure leading Dremio’s global growth.
Quarfoot’s arrival follows Dremio’s announcement last week introducing its Next-Generation Cloud and the industry’s first Agentic Lakehouse, which together expand Dremio’s platform for AI-driven workloads, autonomous data management, and modern open data architectures.
At Confluent, Quarfoot led the global acquisition organization spanning the Americas, Europe, and Asia, overseeing all new-logo GTM strategy and execution across enterprise and digital-native segments. He also led Confluent’s global SDR organization and partnered closely with Marketing and Product-Led Growth teams to strengthen pipeline velocity and adopt emerging AI-driven sales motions.
Before Confluent, Quarfoot held senior sales leadership roles at Datadog, New Relic, and Oracle, where he consistently exceeded expectations, built high-performing enterprise teams, and helped scale cloud consumption and data platform businesses.
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“Matt brings deep experience in cloud, data infrastructure, and modern GTM execution,” said Sendur Sellakumar, CEO of Dremio. “He brings a customer-obsessed mindset that aligns perfectly with how we build and innovate — starting with the customer problem and working backward. His leadership will help us expand our reach and support the momentum we’re seeing across the Agentic Lakehouse.”
“Dremio is uniquely positioned with a forward-looking approach to AI-driven data workloads and an open architecture,” said Quarfoot. “I’m excited to join the company at a time when customers are rethinking their data platforms for the next decade.”
Quarfoot’s appointment strengthens Dremio’s leadership team as the company continues to expand its enterprise footprint and advance its open, cloud-native lakehouse for AI-driven data workloads.
Source: GlobeNewswire
