Data Product Owner (on-site)

Responsibilities

• Own the Enterprise Data POD product roadmap — quarterly priorities, the prioritized backlog, and sprint-level commitments.
• Define and track the Data POD’s two outcome KPIs: Brand Onboarding Velocity and Decision Time to Insight; partner with leadership to set baselines and targets.
• Run backlog refinement, sprint planning, and stakeholder reviews on a regular cadence; keep the team aligned on what’s next and why.
• Translate brand partner needs, internal Sales/CS requirements, and executive priorities into clear product requirements with acceptance criteria.
• Make trade-off decisions and communicate them clearly: what we’re building, what we’re not, why now, what’s next, and what’s blocked.
• Route all ad-hoc data and reporting requests through a prioritized intake — replacing the standalone BI Analyst function and keeping engineers focused on roadmap work.
• Partner with Marketing, Sales, and CS teams to position data products externally — brand-facing demos, Mid-Market analytics pitches, and customer enablement.

Qualifications

• 5+ years of product management experience, with at least 3 years owning data, analytics, BI, or ML products.
• Demonstrated experience setting and tracking product KPIs that the team is actually measured on — not vanity metrics.
• Strong data fluency: comfortable reading SQL, understanding pipeline architecture at a high level, and discussing trade-offs with engineers.
• Experience running an agile backlog (Scrum, Kanban, or hybrid) and using prioritization frameworks such as RICE or weighted shortest job first.
• Strong stakeholder management — comfortable saying “no” or “not now” to executives and brand partners while maintaining the relationship.
• Excellent written communication; able to write PRDs, status updates, decision logs, and executive briefs.

Preferred Experience

• As a Product Owner in a POD, squad, or cross-functional team model — especially launching a POD from scratch.
• Background in restaurant technology, retail technology, hospitality, or an industry with brand-partner / franchise dynamics.
• Familiarity with Databricks, Looker, Tableau, Power BI, Dash, or modern analytics stacks.
• Familiarity with AI products and the unique challenges of owning them — evals, model risk, and slow feedback loops.
• Bachelor’s degree in Business, Engineering, Computer Science, Analytics, or equivalent practical experience.