Principal Product Manager, Data

Procore has the richest construction dataset in the industry. We're looking for a Principal Product Manager, Data to lead the work to turn that data into higher-order data products that make construction companies smarter.

As a Principal Product Manager, Data, your job is to define what we build on top of our core data model, combining Procore data with external construction systems, identifying patterns across hundreds of thousands of projects, and defining curated datasets and predictive models that power AI experiences. We expect this person to become the deepest expert at Procore on construction data - how it's generated across the project lifecycle, how it varies across customer types, what it can predict, and where the gaps are.

Procore manages data across millions of construction projects. This role will add value to that data by building products that combine signals across systems, surface patterns customers can't see today, and turn historical data into forward-looking intelligence.

This position reports to the Senior Director, Data Products and will be based in our San Francisco office. We're looking for someone to join us immediately.

• Define and prioritize curated data products that combine signals across Procore's platform into derived datasets that customers and internal products can act on.

• Identify opportunities for predictive models that turn historical construction data into forward-looking intelligence. Define the data requirements, success criteria, and business cases for each.

• Own the strategy for how Procore data combines with external construction system data to create a more complete picture of project and portfolio performance.

• Work closely with the teams that own Procore's core data model to ensure curated products are well-grounded in the underlying entities and relationships.

• Define data quality, completeness, and validation criteria for derived datasets. Understand what "good data" looks like across different customer configurations and tool adoption levels.

• Partner with product teams across Procore to understand what data products would unlock the most value for analytics, insights, and AI experiences.

• Own APIs and data services that make curated data products available to consuming products and experiences across Procore.

• Make prioritization calls on which data products to invest in next based on customer value and product impact.

• Lead cross-functional collaboration with Engineering, Data Science, Data Engineering, and Go-to-Market teams through all phases of product development.

• Define and track success metrics for data product adoption and business impact across Procore's product portfolio.

• At Procore, AI isn't a specialized tool, it's a core competency. We expect every team member to be AI-literate, leveraging generative tools and agentic workflows to move faster and work smarter. You won't just use AI; you'll be building the agentic future of construction.

• 5+ years of product management or equivalent relevant experience with meaningful time spent on data products, data platforms, analytics infrastructure, or ML/AI products in B2B SaaS.

• Experience defining derived data products or curated datasets - you've taken raw platform data and turned it into something more valuable than the sum of its parts.

• Deep understanding of data modeling concepts - entity-relationship design, semantic models, API design, and the tradeoffs between flexibility and structure. You need to understand a core data model well enough to build confidently on top of it. Experience with cross-system data a plus.

• Ability to take large, complex strategic problems and break them into logical intermediate steps that deliver consistent value.

• Track record of working across many teams without direct authority. You'll need to build relationships, create buy-in, and resolve conflicts when teams have competing data needs.

• Comfort with ambiguity at scale. The construction industry has thousands of workflows across general contractors, specialty contractors, and owners. There is no single "right" way to model derived data - you'll need to make defensible tradeoffs and own them.

• Strong enough technically to review data model designs, evaluate API contracts, and have credible conversations with data engineers and backend engineers. You should be able to look at a dataset and spot what's missing.

• Construction industry experience is a strong plus. You'll need to understand why a change event becomes a commitment change order, why budget line items are planned spend and not actual cost, and why WBS codes matter. If you don't have this background, you need the curiosity and speed to learn a complex domain quickly.

• Demonstrated ability to define initiative-level customer and business outcomes, track progress against them, and explain why they're meaningful.

• Excited to use AI tools to multiply what you and your team can do.

• Excellent written and verbal communication.

Base Pay Range:

This role may also be eligible for Equity Compensation and/or Bonus Incentive Compensation. Procore is committed to offering competitive, fair, and commensurate compensation. Actual compensation will be based on a candidate's job-related skills, experience, education or training, and location.

Procore will consider for employment all qualified applicants, including those with arrest or conviction records, in accordance with the requirements of applicable federal, state, and local laws, including the City of Los Angeles' Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act.

A criminal history may have a direct, adverse, and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment: 1. appropriately managing, accessing, and handling confidential information including proprietary and trade secret information, as well as accessing Procore's information technology systems and platforms; 2. interacting with and occasionally having unsupervised contact with internal/external customers, stakeholders, and/or colleagues; and 3. exercising sound judgment.