Senior Product Manager, Reporting & Analytics in Winnipeg

RocketRez is the revenue maximization platform behind boat tours, theme parks, zoos, and other attractions and experience operators. Operators run their businesses on us: ticketing, capacity, memberships, point of sale, web stores, and the data that tells them how to grow their business.

Your job is to turn operators' questions into data, reports, and visuals that answer them clearly and lead to a revenue maximizing decision. You'll own Reporting & Analytics end to end: the reports, dashboards, and insights operators use to run their business, from the general manager checking yesterday's attendance to the finance lead reconciling a month of revenue across channels, and the data models and metric definitions behind them.

You'll own its roadmap, its customers, and the case for where engineering time goes. Your job is to prove that reporting can be the front door to RocketRez: where operators start their day, and what moves them to act. You'll be measured on usage, and on the revenue operators earn from the decisions reporting drives.

Operators move more of their business onto RocketRez when they trust us with their busiest day, and that trust depends on the numbers. If the reporting is wrong, late, or confusing, nothing else we build gets believed.

• Understand the question: Spend real time with operators across roles, from general managers and finance leads to marketers and front-gate supervisors. Learn the decisions they make and the questions they need answered to make them.
• Design reporting that leads to a decision: Every report should make clear what it means and what to do next.
• Data fluency: Prototype with real data. Write your own SQL to mock up a report or metric and put it in front of operators before engineering builds it.
• Own the metric definitions the platform runs on: revenue, attendance, capacity utilization, and conversion mean the same thing in every report, in every domain.
• Apply statistical judgment: seasonality, small samples, cohorts, fair comparisons, and forecasting.
• Choose the right visual for the question, and hold a high bar for clarity, accuracy, and honest scales.
• Work with other domains so new products capture the data reporting needs before they ship.
• Own the roadmap: sizing, sequencing, and what gets cut.
• Shape how automation and AI turn insights into recommended actions: which recommendations are trustworthy, when a human should decide, and the guardrails around both.
• Define how cross-operator benchmarks work: peer sets, minimum sample sizes, and anonymization that operators trust enough to opt into.
• Make the build, buy, and partner calls on analytics tooling, and know the market well enough to say which gaps are worth closing.

The trait we care about most is adaptability. The tools and methods of product management are changing, so we hire people who can adapt.