The seasoned technology leader will advance Confluent’s platform to power AI, real-time intelligence, and scalable data-driven applications globally.
India, September 9, 2025: Confluent, the global pioneer in data streaming, today announced the appointment of Stephen Deasy as its Chief Technology Officer. In this role, Stephen will shape the company’s engineering vision, strategy, and execution, overseeing the development and scaling of Confluent’s data streaming platform to enable real-time AI, hyper-personalized customer experiences, and automated operations at global scale.
Leadership Speak
Jay Kreps, Co-founder and CEO of Confluent, said: “Stephen brings a wealth of experience scaling engineering teams and building platforms that power the world’s most demanding systems. His leadership will accelerate our mission to help customers transform data streams into a foundation for AI, smarter decision-making, and new classes of real-time applications.”
Stephen Deasy brings over 20 years of experience leading engineering teams at high-growth technology companies. He previously served as CTO at Benchling, where he built global product and platform teams, and held senior engineering roles at Atlassian, VMware, EMC, and Groupon. Stephen also holds multiple patents and invests in early-stage technology ventures.
Commenting on his appointment, Stephen Deasy said: “Confluent is defining what’s possible with streaming data, and I’m excited to be part of that journey. I’ve seen firsthand how real-time data can transform businesses. I look forward to making this powerful technology more accessible and impactful for organizations worldwide.”
About Confluent
Confluent is a leading data streaming platform that enables organizations to set data in motion. Its cloud-native platform acts as intelligent connective tissue, allowing real-time data from multiple sources to flow seamlessly across an organization. Confluent empowers businesses to deliver rich digital customer experiences and implement sophisticated, software-driven backend operations in real time.