Senior Product Manager, Data Foundations

We are building a first-of-its-kind consumer mobile product from the ground up. As a Product Manager, you'll be assigned a specific feature area to own end-to-end the exact scope will be defined based on team needs and your background, and shared in more detail during the interview process from spec to shipped feature to the metrics that tell you whether it worked. There is no legacy roadmap and no bloated process to inherit just a zero-to-one build, a small high-output team, and an AI-native way of working that lets one person do the job that used to take three.

The Product

You'll be part of a small, high-output team building the data infrastructure and BI foundation that powers decision-making across a fast-moving, AI-native organization. This isn't a legacy data team with years of technical debt to untangle, it's a chance to set strategy and architecture for how the entire company understands its own data, working in an AI-native way that lets one person do work that used to take three.

This is a hands-on role for someone who is as comfortable in a data architecture review as they are presenting KPI insights to leadership. You'll work directly with Analytics leadership, engineering, and business stakeholders to turn scattered data and ad hoc reporting into a scalable, trusted system of record.

What You'll Do

• Set strategy and roadmap for our central data infrastructure and BI deployment, partnering closely with Analytics leadership to support company-wide KPI reporting and the development of key insights
• Bring deep understanding of cloud data warehousing (BigQuery, Snowflake, Databricks, or similar) to inform architecture and platform decisions
• Apply strong understanding of semantic layers and data modeling to support advanced, reliable analysis across the business
• Own and evaluate BI and ETL tooling and techniques, ensuring the stack scales with the company's needs
• Deeply understand user workflows and drive adoption through clear requirements docs, quality and timeliness SLAs, and rapid prototyping of reporting and query capabilities
• Identify and implement AI-based solutions that democratize insight production, enabling business users without technical query skills to self-serve answers
• Translate ambiguous business and analytics needs into clear, testable requirements that engineering can build against

Who You Are

• Experienced Operator: You've owned data platform or BI product strategy end-to-end, from architecture decisions through adoption
• Technical: You're fluent in cloud data warehousing, semantic modeling, and BI/ETL tooling, enough to make informed architecture calls and hold your own in technical conversations with data engineers
• AI-First: You already use AI tools as part of your daily workflow, and you actively look for ways AI can widen access to insights across the business, not just automate existing reports
• Structured Thinker: You can take an ambiguous, cross-functional need and turn it into a clear, sequenced set of requirements with no gaps
• Data-Driven: You define what "good" looks like (SLAs, adoption metrics) before you build, and use the numbers to guide iteration
• Scrappy & Scaled: You're comfortable building foundational systems with a lean team, with enough experience to anticipate what breaks as usage and data volume grow
• Action-Oriented: You default to shipping and prototyping over lengthy internal review cycles

What Success Looks Like

• Business teams across the company trust and rely on a single source of truth for KPI reporting
• Non-technical stakeholders can self-serve insights without needing to write a query
• Reporting and data requests move faster, with clear SLAs on quality and turnaround
• The data platform scales cleanly as usage, data volume, and business complexity grow

Location: Bay Area - Reporting To: Director of Product: $153k - $203k base + equity + benefits