Senior Product Manager, AI Data Foundation

ZoomInfo is where careers accelerate. We move fast, think boldly, and empower you to do the best work of your life. You’ll be surrounded by teammates who care deeply, challenge each other, and celebrate wins. With tools that amplify your impact and a culture that backs your ambition, you won’t just contribute. You’ll make things happen–fast. ZoomInfo is seeking a Sr Product Manager, AI Data Foundation to own our data quality monitoring platform, self-service reporting capabilities, and the internal tooling that powers data research and analysis across the organization. In this role, you'll work at the intersection of AI, data quality, and platform product management - building systems that make ZoomInfo's data teams faster, smarter, and more proactive. The Sr PM, AI Data Foundation will be an evangelist and builder, not a reactive order-taker. You'll see across the full data portfolio, identify opportunities for extreme leverage, and drive AI-enabled solutions for data quality enhancement and self-remediation. This role is critical to ZoomInfo's ability to scale data quality at speed and empower teams with the tooling they need to move faster.

What You'll Do (Essential Functions)

Own end-to-end product strategy for data quality monitoring, self-service reporting, and the internal Data Tools platform Proactively identify opportunities across the data portfolio where tooling and automation can create extreme leverage for data teams, PMs, and analysts Define and standardize metrics and KPIs for data quality, coverage, accuracy, and freshness across all data domains Build and deliver self-service dashboards and reporting tools that give stakeholders real-time visibility into data health Identify, prioritize, and ship AI-driven data quality enhancements and auto-remediation capabilities that reduce manual intervention at scale Own the internal Data Tools roadmap, delivering tooling that meaningfully improves productivity for data researchers, analysts, and product managers Partner with engineering and data science to develop AI-powered solutions for anomaly detection, root cause analysis, and self-healing data pipelines Drive adoption of new tooling across data operations, engineering, and PM teams through evangelism, documentation, and enablement Manage dependencies across data domains to ensure quality monitoring integrates seamlessly with upstream and downstream systems Conduct discovery with internal stakeholders to uncover true tooling and workflow pain points beyond surface-level feedback