What you will own
• Two adjacent problem spaces, sized so one thoughtful PM can hold both without either getting neglected: Platform (payments, payment plans, refunds and chargebacks, group billing, financial aid, third-party financial partnerships like trip protection and financing) and Data (data quality, pipelines that feed reporting and personalization, self-serve analytics for internal teams, instrumentation the experimentation program depends on).
• Product ownership of our Microsoft Fabric migration and Power BI surface — helping define what “good” looks like for internal data consumers, what use cases the platform must serve, and how we prioritize the migration so it delivers value along the way rather than only at the end.
• The full discovery-to-outcome loop across both spaces: who the customer is (families, schools, internal finance, internal data consumers), what is broken, what is worth solving, what we will try, what we learn, what we double down on.
• Day-to-day partnership with pods in each area — dedicated engineers and shared collaborators (design, research, data engineering, finance business partners, compliance) whose time you will share with other PMs. Earning their best work is part of the job.
• Cross-space sequencing. Platform outcomes often depend on the data foundation being right first — you will know when that’s true and when it isn’t.
• A portfolio of live experiments across both spaces, with explicit hypotheses, success thresholds, and kill criteria.
• Quarterly outcome targets tied to money and trust — payment success, time-to-first-payment, chargeback rate, data self-service response time, data quality SLAs — not output volume.
What you will do
• Frame problems sharply across two lanes. Synthesize customer research, transactional data, finance conversations, and internal user interviews into problem statements precise enough that the team can disagree productively. Toggle context between spaces without losing depth in either.
• Treat internal users like customers. Data platform work has customers inside the company — analysts, ops teams, PMs, marketing, finance. Understand their jobs, prototype your solutions in Power BI or lightweight tools, measure outcomes the same way you would for an external user.
• Shepherd the Fabric migration from the product side. Partner with data engineering on the migration to Microsoft Fabric — sequencing which domains and use cases move first, defining semantic models and Power BI surfaces that internal teams will actually adopt, and making sure the migration ships incremental wins rather than a big-bang cutover.
• Design experiments. Translate problem frames into the smallest tests that would change your mind. Default to many small bets over one big one — even in finance and data, where the instinct is to plan large.
• Use AI as a force multiplier. Draft schemas, generate SQL and DAX, summarize financial policy documents, synthesize interview transcripts, prototype internal tools, and pressure-test your own thinking. You don’t need to have shipped AI features; you do need to actively use AI in how you work.
• Judge slowly and deliberately. Set explicit outcome thresholds before tests run. Be honest about signal vs. noise. Kill ideas — including your own — that don’t clear the bar.
• Sequence strategically across spaces. Ensure each experiment compounds: financial infrastructure and data assets that future bets can build on, not one-off wins.
• Navigate regulatory and compliance edges. PCI, financial reporting, data governance, PII handling. You don’t need to be a lawyer, but you know when to bring one in — and you build controls into product decisions early, not bolted on later.
• Communicate up and across. Tell leadership, your pods, finance, data, and compliance a clear, honest story about what we are learning, where we are betting, and where we are stuck.
• Make shared resources want to work with you. Designers, engineers, and business partners split their attention across pods. You earn their best thinking by bringing sharp problems, respecting their craft, and being a generous teammate — not by competing for their time.