Principal Product Builder, Data

Role overview

Own the product strategy and delivery for a B2B data catalog that supports sales and marketing workflows. The role spans data quality, sourcing, measurement, and the ways data is represented across product features and customer systems. You will work across product, engineering, design, research, data science, and customer-facing teams to make the catalog more accurate, useful, and trustworthy.

Responsibilities

- Set the vision, roadmap, and priorities for the core data catalog, connecting initiatives to business goals. - Learn from customers, go-to-market teams, support, and internal users to identify coverage, accuracy, freshness, and usability gaps. - Establish metrics and dashboards for catalog breadth, depth, accuracy, and freshness, and use them to guide decisions. - Develop an ongoing approach to finding, assessing, and integrating data sources; lead build, buy, or partner evaluations. - Define how data appears across search, enrichment, filters, scoring, APIs, and customer systems, including its taxonomy and structure. - Partner with technical and customer-facing teams on architecture, reliability, data trust signals, evaluations, and product improvements. - Prototype ideas with AI-enabled tools and write clear strategy, requirements, launch, and tradeoff documents.

Requirements

- At least seven years of product management experience, including ownership of complex data products from strategy through launch. - Principal-level ownership of a significant product area and strong judgment in prioritization and tradeoffs. - Hands-on use of AI-native tools to prototype and validate ideas, with examples of work built or shipped. - Ability to reason about multiple data sources, aggregation, catalog performance, and data-backed product metrics. - Technical fluency in architecture, APIs, data models, reliability, observability, instrumentation, and edge cases. - Working understanding of privacy, consent, licensing, and regulations such as GDPR and CCPA. - Customer empathy for the impact of missing, stale, or inaccurate data on business workflows.

Nice to have

Experience building products for sales, marketing, revenue operations, or customer success; managing data vendors; and using analytics, experimentation, or support insights to improve data quality.

Benefits and work setup

The listing describes equity, possible bonus compensation, retirement savings, paid holidays, flexible time off, parental leave, wellbeing resources, insurance, and medical, dental, and vision coverage. Pay varies by location and experience.