COMPANY INFO
Databricks, Inc. is a private company founded in 2013 by Ali Ghodsi, Ion Stoica, Matei Zaharia, Patrick Wendell, Reynold Xin, Andy Konwinski, and Arsalan Tavakoli-Shiraji. It operates in the computer software industry with approximately 8,000 employees as of 2025, headquartered in San Francisco, California, and its website is databricks.com. Databricks provides a cloud-based data and AI platform that unifies data engineering, analytics, and machine learning on a lakehouse architecture, enabling organizations to manage and utilize both structured and unstructured data for business analytics and AI workloads. The company is known for pioneering the data lakehouse concept and developing open-source projects like Apache Spark and Delta Lake.
Databricks, Inc. is a leading private technology company headquartered in San Francisco, California, specializing in cloud-based data engineering, analytics, and artificial intelligence. Renowned for pioneering the data lakehouse architecture and developing open-source projects like Apache Spark and Delta Lake, Databricks empowers organizations worldwide to unify and leverage their data for advanced business analytics and AI workloads.
Databricks, Inc. executives comprise a dynamic mix of founders, technologists, and industry veterans, credited with shaping the company's vision and culture since its inception in 2013. With deep expertise spanning distributed systems, advanced analytics, product management, security, and go-to-market strategy, the Databricks leadership team has transformed the company into a global force in data, AI, and cloud computing—scaling from a UC Berkeley spinout to serving over 10,000 organizations and exceeding $1.6 billion in annual revenue.
As CEO, Ali Ghodsi leads Databricks, Inc.’s company-wide vision and long-term strategy, driving innovation in data lakehouse, AI, and cloud-native products. A champion of open-source collaboration, Ali has steered Databricks through strategic partnerships with Microsoft Azure and Google Cloud, expanded into generative AI with MosaicML, and overseen global growth—culminating in revenue reaching $1.6 billion in 2023.
Ali earned his PhD in Machine Learning from KTH Royal Institute of Technology and has held roles as Adjunct Professor and Visiting Scholar at UC Berkeley. Prior to founding Databricks, he was VP of Engineering & Product Management for precursor projects and co-created Apache Spark at Berkeley’s AMPLab, cementing his reputation as a leader in big data, distributed systems, and AI research.
Matei Zaharia is the driving force behind the technological and research roadmap at Databricks, Inc., leading the creation and evolution of platform components including Apache Spark, Delta Lake, and MLflow. As CTO, he directs innovation in cloud computing, large-scale data infrastructure, and generative AI, advancing signature projects such as Dolly and ColBERT for open-source AI.
Matei holds a PhD in Computer Science from UC Berkeley, where he founded Apache Spark in 2009. He continues as an Associate Professor at Berkeley and is recognized with accolades like the ACM Doctoral Dissertation Award and NSF CAREER Award, demonstrating world-class expertise in distributed computing and open-source framework development.
As Executive Chairman, Ion Stoica provides strategic oversight, corporate governance, and guidance on M&A and R&D priorities at Databricks, Inc. He was instrumental in securing key funding rounds—like the $10 billion Series J at a $62 billion valuation—and building alliances with tech leaders such as Anthropic.
Ion earned a PhD in Computer Science from UC Berkeley, where he has also served as Professor and Department Chair. In addition to co-founding Databricks, he co-founded Conviva and NetSeer, bringing decades of experience in cloud infrastructure, networking, and distributed data systems.
Patrick Wendell leads the engineering team at Databricks, Inc., ensuring the development, performance, and operational reliability of the company’s core platform for global enterprise customers. He has been pivotal in scaling Spark and the Lakehouse architecture, driving operational improvements and high-quality product delivery.
Patrick holds a BS and MS in Computer Science from UC Berkeley and was an early innovator in the Berkeley AMPLab, co-authoring critical Spark components. His background includes deep contributions to open-source and proficiency in managing distributed systems and engineering teams at scale.
Reynold Xin oversees product vision and management at Databricks, Inc., guiding the development and commercialization of core offerings such as Spark, Delta Lake, MLflow, and AI model tooling. Reynold led groundbreaking releases like Spark SQL and Delta Lake 2.0, helping Databricks achieve widespread industry adoption.
Reynold earned his PhD in Computer Science from UC Berkeley, where he co-created fundamental Spark APIs and contributed as a research scientist at the AMPLab. His expertise lies in analytics, real-time data processing, and designing next-generation data and machine learning products.
Arsalan Tavakoli-Shiraji architects Databricks, Inc.’s security strategy and leads frameworks for compliance and governance, enabling enterprise-grade cloud deployments. He has led the company through key certifications and launched powerful automated compliance tools for highly regulated customers.
Arsalan holds an MS in Computer Science from UC Berkeley. As an architectural contributor to Spark’s security at AMPLab and a co-founder of Databricks, his background includes security consulting and extensive work in distributed and secure computing.
Dave Conte is responsible for Databricks, Inc.’s financial planning, investor relations, and capital management, having overseen transformative funding rounds—including the $10 billion Series J—and guided the company towards financial discipline and profitability.
Dave has a BS in Business Economics from UC Santa Barbara. With previous CFO roles at Splunk and IronKey and as a board member at Anaplan, he offers significant expertise in SaaS financial operations, IPO preparation, and scaling high-growth technology organizations.
Rick Schultz leads global marketing, brand strategy, and product positioning for Databricks, Inc., elevating the company as the category creator for the data lakehouse. He has engineered the Data + AI Summit into an industry-leading event and driven brand awareness to support hyper-growth.
Rick holds a BS from UC Berkeley’s Haas School of Business. He was previously SVP Marketing at Alteryx and has led marketing at Splunk and Salesforce Ventures, with a career focus on SaaS, GTM strategy, and technology brand building.
Robin Sutara defines data strategy for Databricks, Inc.’s enterprise customers, championing field advisory services that drive successful adoption of Databricks Lakehouse and AI solutions. She established the innovative Data Strategy Officer program to optimize large-scale customer implementations.
Robin has a Graduate Certificate from Stanford University and has held leadership and advisory roles at Bridgewater Partners and other premier data organizations. Her expertise spans data governance, AI strategy, and customer success initiatives.
Dael Williamson steers technology strategy and pre-sales engineering across Europe, the Middle East, and Africa for Databricks, Inc., customizing Lakehouse deployments and building regional R&D teams to accelerate growth and adoption.
Dael earned an Executive Leadership certificate from INSEAD and brings advisory experience from initiatives like BIORCE and Frugal AI Hub. He has led pivotal roles in scaling cloud and AI technologies across international markets.
The Databricks, Inc. leadership team is deeply rooted in technical innovation, founded by UC Berkeley alumni and AMPLab researchers, and augmented by accomplished executives in finance, marketing, and global operations. This blend of expert co-founders and seasoned industry leaders ensures Databricks remains at the forefront of the cloud data, analytics, and AI landscape, with a management team known for agility, technical acumen, and a collaborative approach to scaling global impact.
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