Principal Product Manager - Vertical Data

ZoomInfo is a go-to-market intelligence platform that provides AI-ready insights, trusted data, and automation to help businesses grow. The Principal Product Manager will own the full lifecycle of vertical datasets, including development, platform delivery, pricing, packaging, commercialization, and revenue generation. The role also involves working with strategic customers, sales, data, engineering, pricing, legal, and marketing teams to build and sell data-driven solutions.

Responsibilities:

• Define what the dataset is and who it's for. Source the data (public records, partner licensing, our own extraction and classification). Set the bar for coverage, accuracy, and entity resolution against ZoomInfo's company and contact graph, and work with our data analysts to hit it. Decide what "done" looks like for a dataset and hold the line on it
• Partner with data engineering and platform engineering to get datasets out of the warehouse, into the GTM Data Store, and live across every surface: our APIs, MCP, and our applications. Write the requirements, define the use case queries, own the testing, drive the handoffs. This is the stage where most data products die. You'll make sure ours don't
• Own pricing and packaging: how a dataset shows up in the price book, what's licensed in bulk versus consumed per record, what needs supplemental terms, how it bundles with core data and with other vertical datasets. We're investing more and more in the product-led motion alongside the sales-led one, so this means enabling both: making datasets discoverable and consumable in-product, and building the sales materials our teams need to sell them by vertical: enablement content, data reference guides, use cases, positioning. Then go sell with them
• Sit with sales on the accounts that matter. Get in front of customers, understand what they're actually trying to do with the data, and shape the dataset and the offer to fit. Some of this is presenting. A lot of it is listening and then going back and changing the product
• Figure out how UCC filings and commercial property data become a prospecting workflow for a commercial banker, or how Form 5500 and insurance producer data become a cohesive platform for the benefits and insurance market. Package datasets into something a vertical buyer recognizes as built for them
• You're the person who knows where a dataset stands at every stage and is accountable for moving it forward. That means working with analysts on data quality, with engineering on delivery, with pricing and legal on terms, and with marketing on how it shows up in market
• There are more datasets we could build than we can build well. You'll help decide which ones get investment based on revenue potential, customer pull, and what makes the core data more valuable
• What you learn from customers goes back into what we build next. What you learn from delivery goes back into how we build faster

Requirements:

• You've owned a number, or been close enough to one that it changed how you prioritized
• You've spent real time in front of customers: enterprise product management with a lot of customer contact, solutions consulting, professional services, or a customer-facing role at a data company
• You've taken multiple datasets and turned them into a product or workflow that served a specific market, ideally in financial services, insurance, or another data-heavy vertical
• Discovery, requirements, working with engineers, launch, enablement, pricing, and the unglamorous work of getting something actually shipped across multiple teams
• Principal here means you can run the whole thing without a lot of scaffolding
• You can work in SQL, you understand entity resolution and the tradeoffs between coverage, accuracy, and freshness, and you can look at a dataset and form your own opinion about whether it's any good
• You take responsibility for outcomes, not deliverables
• You move fast, make calls with incomplete information, and don't wait for process to exist before getting things done
• Your first instinct should be to reach for AI tools to work fast and produce an incredible amount of output
• We use Claude Code and similar tools across the team for building, analysis, and writing, and you should be comfortable working that way
• Experience with B2B data, data licensing, or data-as-a-service is a strong plus
• Experience with public records, regulatory filings, or vertical-specific data sources is a plus too