Hiring.fm
Hubspot

Senior Product Manager, Data and Insights

Remote - USA Full Time
POS-15751

Role Summary

Our mission at HubSpot is to help millions of organizations grow better.

Product usage data informs critical decisions across HubSpot, powering initiatives like AI-driven engagement, experimentation, activation metrics, and financial reporting. Hundreds of teams across every HubSpot product rely on high-quality event data to understand customer behavior, measure outcomes, and guide product and business strategy.

As a Senior Product Manager on the Customer Journey Engage Product Group, you’ll shape the future of HubSpot’s usage data platform. You’ll define how teams instrument, discover, govern, and operationalize usage data, enabling reliable analytics, experimentation, and AI-powered insights. This role sits at the intersection of platform infrastructure, analytics, and product strategy — helping teams across HubSpot make better decisions and deliver more value to customers.

What You’ll Do

  1. Own the product vision and roadmap for HubSpot’s usage data platform, shaping how teams instrument, discover, and operationalize product usage data.

  2. Define and evolve the systems that power HubSpot’s event pipeline and analytics infrastructure, ensuring data is reliable, governed, trustworthy, and scalable across hundreds of teams.

  3. Treat data as a product by establishing clear data models, instrumentation standards, and lifecycle governance that enable trustworthy analytics, experimentation, and AI-driven applications.

  4. Partner with Engineering, Analytics, Product Operations, Machine Learning, and Design teams to build tools that power HubSpot’s analytics ecosystem, experimentation platform, recommendation systems, and engagement initiatives.

  5. Improve how internal teams explore and operationalize usage insights by enabling clearer metrics, streamlined workflows, and self-service analysis without sacrificing governance or data quality.

  6. Lead complex platform initiatives from concept through implementation and adoption, balancing technical constraints with product and business outcomes.

  7. Serve as a subject matter expert on product usage data, helping teams understand how instrumentation, experimentation, and analytics systems work together to drive customer outcomes.

  8. Align diverse stakeholders across the company, driving progress in ambiguous environments and delivering initiatives with clarity and speed.

What You’ll Bring

Required Qualifications

  • Experience building or owning platform, data, or analytics products that serve internal teams or developers.

  • Strong systems thinking with the ability to understand how data pipelines, instrumentation, analytics tooling, and downstream applications interact.

  • Experience partnering closely with engineering and analytics teams to define scalable solutions to complex technical challenges.

  • Ability to balance governance, consistency, and data quality with usability, flexibility, and self-service capabilities for internal users.

  • Strong product judgment and the ability to make tradeoffs across technical, business, and user considerations.

  • Experience leading initiatives across diverse stakeholders and driving alignment in ambiguous environments.

  • Excellent communication and collaboration skills, with the ability to translate complex technical systems into clear product direction.

  • Comfort making decisions, testing assumptions, and iterating quickly in fast-paced environments.

  • Experience working with product analytics platforms (e.g., Amplitude, Mixpanel, Pendo) and querying datasets using SQL to inform product decisions.

  • Strong empathy for internal users and the ability to balance multiple personas when designing platform products.

Nice-to-Have Qualifications

  • Experience building experimentation platforms, recommendation systems, or AI-ready data platforms.

  • Experience designing event instrumentation frameworks or analytics governance models.

  • Experience working with large-scale data infrastructure or data platforms in SaaS environments.

  • Familiarity with machine learning pipelines or data systems supporting AI-driven products.

Where You’ll Work