Partner Business Intelligence

About the Team

OpenAI’s mission is to build safe artificial general intelligence (AGI) that benefits all of humanity. This long-term undertaking brings the world’s best scientists, engineers, and business professionals together to advance AI responsibly and ensure its benefits are broadly shared.

OpenAI’s Go-To-Market (GTM) Partnerships team builds and scales a global ecosystem of strategic partners that accelerate AI adoption, expand customer impact, and extend OpenAI’s reach across industries and geographies. As the Partnerships organization rapidly expands, data has become a critical strategic asset. The ability to accurately measure partner influence, attribute customer outcomes, track performance against targets, and administer partner incentives is foundational to how OpenAI scales its ecosystem.

The Partner Business Intelligence team sits at the center of this effort, building the data infrastructure, attribution systems, reporting frameworks, and analytical foundations that power decision-making across the Partnerships organization.

About the Role

We are seeking a highly technical and business-minded leader to build and own the data foundation of OpenAI’s global Partnerships organization.

This role will be responsible for designing, building, and governing the Partnerships data model that serves as the source of truth for partner performance, attribution, pipeline influence, partner-sourced and partner-influenced revenue, incentive programs, forecasting, and executive reporting.

You will own the end-to-end architecture that powers how OpenAI measures partner impact internally and how we communicate performance externally to partners. This includes designing attribution methodologies, defining performance metrics, building scalable data pipelines, establishing reporting frameworks, and creating the infrastructure that supports partner incentive calculations and payouts.

This is a uniquely high-impact role. As OpenAI scales its partner ecosystem, the accuracy and integrity of our attribution framework will directly influence hundreds of millions of dollars in partner incentives and strategic investments. Over the next year, we expect approximately $XXXM in partner incentives, with roughly $XXXM directly dependent on the attribution systems and performance infrastructure owned by this team.

The ideal candidate combines deep expertise in analytics engineering, business intelligence, data modeling, and executive stakeholder management with the ability to translate complex business relationships into scalable and auditable systems.

In This Role, You Will

Build and Own the Partnerships Data Foundation

• Design and maintain the canonical Partnerships data model across partners, opportunities, customers, revenue, incentives, competencies, activities, and performance metrics

• Establish the authoritative source of truth for partner-sourced, partner-influenced, co-sell, marketplace, and ecosystem-driven business

• Define data governance standards, metric definitions, and reporting methodologies across the Partnerships organization

• Create scalable frameworks that support evolving partner motions, business models, and incentive structures

Develop Attribution and Performance Infrastructure

• Design and continuously evolve OpenAI’s partner attribution methodology across complex multi-party sales motions

• Build the systems and logic used to measure partner contribution throughout the customer lifecycle

• Create auditable frameworks for determining partner influence, sourcing, acceleration, and value creation

• Partner closely with Finance, Revenue Operations, and Partnerships leadership to ensure attribution methodologies are trusted, scalable, and financially defensible

Build Incentive and Payout Infrastructure

• Develop the measurement systems that underpin partner incentive programs and financial payouts

• Create scalable processes for incentive calculation, validation, reconciliation, and reporting

• Ensure incentive-related metrics are transparent, explainable, and auditable

• Support forecasting and planning processes tied to partner investment and incentive budgets

Deliver Business Intelligence and Executive Insights

• Build dashboards, reporting frameworks, and analytical tools used by executive leadership and field teams

• Define and track partner performance targets, KPIs, and organizational scorecards

• Develop forecasting models that support strategic planning and investment decisions

• Generate insights that drive ecosystem growth, partner productivity, and GTM effectiveness

Build Data Products for Internal and External Stakeholders

• Design partner-facing reporting experiences and data products

• Establish frameworks for sharing performance metrics and business outcomes with strategic partners

• Balance internal operational requirements with external partner reporting needs

• Create scalable approaches for delivering trusted and actionable data to ecosystem stakeholders

Partner Cross-Functionally

• Collaborate closely with Partnerships, Revenue Operations, Finance, Data Engineering, Systems, Product, and Strategic Finance teams

• Translate business requirements into scalable technical solutions

• Drive alignment around metric definitions, attribution methodologies, and reporting standards

• Serve as the primary authority on Partnerships data architecture and performance measurement
  

You Might Thrive In This Role If You Have

• 8+ years of experience in business intelligence, analytics engineering, data engineering, revenue operations, or related analytical functions

• Extensive experience designing complex data models and scalable reporting architectures

• Deep expertise in SQL, data warehousing, business intelligence platforms, and modern analytics stacks

• Experience building attribution frameworks for complex enterprise GTM motions

• Strong understanding of revenue operations, sales analytics, pipeline management, and performance measurement

• Experience designing incentive measurement systems, commission frameworks, or financial attribution models

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