Senior Product Manager, AI Data Foundation

What You'll Do

• 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

What You Bring

Required Qualifications

• 5+ years of product management experience with a focus on data products, platforms, internal tooling, or data-intensive B2B SaaS
• Demonstrated experience building data quality, monitoring, observability, or self-service analytics products
• Proven ability to identify and ship AI/ML-powered product capabilities, particularly applied to data quality, automation, or workflow tooling
• Strong understanding of data quality frameworks, metrics, anomaly detection, and the systems that produce and monitor data at scale
• Platform and tooling product mindset with experience driving adoption across diverse internal user bases
• Strong analytical skills with ability to independently define metrics, analyze data, and make data-driven decisions
• Ability to solve complex technical problems in partnership with engineering and data science teams
• Excellent communication skills with ability to translate complex technical concepts for diverse audiences and write clear PRDs
• Proactive orientation - demonstrated ability to identify leverage opportunities across a portfolio, not just respond to inbound requests
• B2B SaaS experience, preferably in data platforms, developer tools, or data operations

Preferred Qualifications

• Experience with data observability, data catalog, or data governance platforms
• Background in data engineering, analytics engineering, or data science prior to product management
• Familiarity with modern data stack tooling (dbt, Snowflake, Databricks, Fivetran, etc.)
• Experience building AI-powered automation or self-remediation capabilities
• Knowledge of data privacy regulations (GDPR, CCPA) and their product implications