Staff Product Manager, Data

Built is the AI-first platform for construction and real estate finance, managing over $300 billion in annual capital for more than 340 lenders, including 45 of the top 100 U.S. banks. Every draw, inspection, budget change and payment that moves through Built leaves behind data our customers need to manage risk and run their portfolios. Turning that data into products lenders rely on every day is one of the biggest opportunities in front of us.

We're hiring a Staff Product Manager, Data to own the data capabilities and reporting tools that sit on top of the Built platform: embedded reporting and analytics, portfolio insights, data delivery into customer systems, and the data foundation our AI features depend on. You'll work alongside data engineering, analytics, and the product teams whose workflows generate and consume the data, and you'll be accountable for ensuring our core products deliver data value to customers.

You’ll directly manage two data scientists and two technical analysts while partnering closely with data engineering and application product teams. Your scope spans reporting and analytics, as well as turning data science work into useful customer-facing capabilities such as construction budget benchmarking and risk insights.

You own a meaningful product area end-to-end with limited direction. You set the roadmap for your space, make the tradeoff calls, and bring stakeholders along with clear reasoning.

Our Guiding Principles

• Be Bold. We pursue the biggest problems in our industry, challenge assumptions others take for granted, and take calculated risks to get there. We don’t hide behind consensus or committees. Playing it safe is just failing slowly.
• Help Customers Win. We learn our customers’ businesses deeply — how they think, how they deploy capital, what keeps them up at night. We treat their capital like our own. We ship leverage, not features. And we measure ourselves by customer results, not our intentions.
• Move with Urgency & Purpose. We bias toward delivery over perfection, remove friction from our own paths, and communicate in real time. Momentum compounds — and we build it every day.
• Own the Outcome. We own outcomes, not just tasks. We hold a high Say:Do ratio and take responsibility from idea through impact. When something breaks, we fix it — we don’t wait to be asked.
• Never Satisfied. We raise the bar continuously. We stay curious, hold exacting standards, debate hard, and hold our opinions loosely when the evidence shifts. Excellence is a habit, not an event.

What You’ll Do

• Own the strategy and roadmap for Built’s data capabilities, including embedded reporting and analytics, portfolio dashboards, data exports, and data sharing integrations.
• Get close to how lenders, owners, and GCs use data to make decisions, and turn that into sharp problem statements and requirements.
• Partner with data engineering on data models, pipelines, and data quality so the numbers customers see are accurate and on time.
• Drive shared metric definitions so a figure like “percent complete” or “funds disbursed” means the same thing in every product and every customer workspace.
• Work with the CLA, CLA+ and payments product teams so data is captured well at the source instead of cleaned up downstream.
• Shape the data that powers Built’s AI features, including the AI Draw Agent and lender portfolio risk tools.
• Track adoption and impact of your products and use what you learn to decide what to build next.
• Support sales and customer success with demos, customer conversations, and enablement on platform reporting and data features.
• Manage and develop a team of data scientists and technical analysts, setting clear priorities and balancing ongoing reporting needs with new feature development.
• Guide data science initiatives from customer problem definition through validation and delivery, partnering with data scientists and engineers to turn models and insights into reliable features within Built’s products.

What You’ll Bring

• 5–8 years of product management experience, with at least 2 years owning data, analytics or reporting products in B2B SaaS.
• Strong SQL and comfort working directly in the data. You can answer your own questions and validate what engineering builds.
• Working knowledge of modern data stack concepts: warehouses, ELT, dimensional modeling, and BI or embedded analytics tools such as Sigma, Looker or Tableau.
• Experience writing requirements for data work that a data engineer can build against, including metric definitions, data contracts and acceptance criteria.
• A track record of shipping data features and analytics capabilities that customers adopt.
• Ability to explain data concepts clearly to bankers and engineers alike.
• Experience partnering directly with data scientists to deliver customer-facing capabilities, with enough fluency in statistical analysis, modeling, and validation to evaluate tradeoffs and explain results and limitations clearly.
• Experience leading work with analysts on reporting and analytics products. Prior people management experience is a plus; readiness to coach and develop data scientists and technical analysts is essential.
• Experience in financial services, lending, real estate, or construction is a strong plus.

What Success Looks Like at Six Months

• You’ve published a data roadmap that product, engineering, and go-to-market leaders have bought into.
• At least one data feature improvement has shipped, and you can show its adoption with real usage numbers.
• Core reporting metrics have agreed definitions and named owners, and customer escalations about numbers not matching are trending down.
• Product teams across the business treat you as their partner for anything data-related.

AI & Technology Expectations

• Leverage AI tools to enhance the productivity, quality, and speed of your work.
• Use AI to support drafting, analysis, summarization, and problem-solving across your role.
• Identify opportunities to streamline workflows and reduce manual effort through automation and AI.
• Apply AI to sharpen decision-making and strengthen strategic insights.
• Share effective AI use cases and best practices with your team.

Built’s salary range for this position is $165,000 - $210,000 USD per year. The pay range is designed to accommodate upward mobility in the role, therefore it encompasses the full span of proficiency levels for this role and we believe that the midpoint of the range is competitive in the market. Salary is just one component of Built's total compensation package for employees; your total rewards package at Built will include equity, market-current medical, dental and vision coverage, an unlimited PTO policy, and other benefits.