Veterans of the world's leading data platforms, united by a shared vision for the future of enterprise analytics.
A team with deep roots in data infrastructure, AI research, and enterprise software — built to solve the hardest problems in analytics.
Chief Executive Officer & Co-Founder
Former VP of Data at Snowflake, where he scaled the analytics platform to serve 5,000+ enterprise customers. James oversaw the growth of Snowflake's core data sharing and marketplace products before founding Dataova to bring next-generation AI intelligence to the enterprise data stack. He holds an MBA from the Wharton School and a BS in Statistics from UC Berkeley. James is a frequent speaker on data strategy and enterprise AI adoption at industry conferences including Strata Data and DataEngConf.
Chief Technology Officer & Co-Founder
Distinguished engineer from Databricks where she was a core architect of the Delta Lake processing engine that now powers hundreds of petabytes of enterprise data. Sofia has pioneered advances in real-time streaming architecture and query optimization for distributed systems at petabyte scale. Her research on incremental query processing has been cited in leading database conferences. At Dataova she leads all platform engineering, setting the technical direction for the query engine, AI inference layer, and data connector ecosystem.
Head of Data Science & Co-Founder
Previously led AI research at Palantir where he built automated insight discovery systems for government and enterprise customers processing sensitive, high-stakes datasets. Michael specializes in natural language interfaces for business intelligence, including the proprietary NLP engine that powers Dataova's plain-English query capabilities. He has published research in natural language processing and knowledge graph reasoning. Michael holds a PhD in Computer Science from MIT and advises several AI research initiatives at leading universities.
Dataova is a remote-first, results-oriented team that values intellectual curiosity, clear communication, and a relentless focus on customer outcomes.
Our team spans multiple time zones. We build the kind of asynchronous, documentation-driven culture that lets exceptional people do their best work from anywhere.
Every team member receives an annual learning budget, access to top conferences, and dedicated time for open-source contribution and personal research projects.
Our engineers work directly with customers. Understanding real-world data challenges firsthand makes us sharper engineers and drives better product decisions.