Product Manager II, Data Platform

Product Manager II, Data Platform 

Introduction to the team 

Join Expedia Group’s Data Platform organization, part of Platform & Data, where we are building a trusted, AI-native foundation for analytics, machine learning, and AI across the company. Our metrics platform team owns the end-to-end lifecycle of business metrics at EG — from how they are defined, governed, and computed, to how they are discovered and consumed by analysts, engineers, product teams, and AI systems company-wide. We are looking for a Product Manager II who thrives at the intersection of data infrastructure and business impact, and who enjoys translating complex platform challenges into products that improve trust, speed, and decision-making at scale. 

In this role, you will: 

• Drive product execution for our metrics platform — a semantic layer that serves as the single source of truth for business metrics across the company, powering executive reporting, self-serve analytics, A/B experimentation, and AI-driven use cases. 

• Own and evolve the product roadmap for the full metrics lifecycle: metric definition and governance, automated computation pipelines, metric discovery and cataloging, and consumption APIs and tooling integrations. 

• Partner closely with engineering, analytics, and business stakeholders to translate complex technical and organizational needs into clear product requirements, prioritized backlogs, and measurable outcomes. 

• Drive adoption of the metrics platform across analytics, product, and engineering teams — identifying friction in how teams define, onboard, and reuse metrics, and building scalable solutions that reduce duplication and improve consistency. 

• Proactively identify gaps in business-critical metric coverage and work with data owners to define and onboard those metrics to the platform. 

• Use qualitative feedback and quantitative signals — including adoption rates, pipeline reliability, and cost efficiency — to prioritize backlog items, evaluate trade-offs, and iteratively improve the platform. 

• Partner with product owners across the data platform to drive integrations that extend the metrics platform’s reach and value to downstream tools and consumers. 

• Shape the platform’s AI strategy: define and deliver features that integrate the metrics semantic layer with AI agents and LLM-based tooling, enabling governed, accurate metric access for AI-driven analytics use cases. 

• Contribute to narratives, documentation, and stakeholder communications that articulate platform value and drive alignment across technical and non-technical audiences. 

Minimum Qualifications: 

• 2+ years of product management experience in a technology-driven environment, with accountability for delivering platform or data infrastructure products. 

• Experience partnering with engineering and cross-functional teams to define requirements, prioritize work, and ship enhancements in iterative releases for internal or platform users. 

• Demonstrated ability to use data, customer feedback, and product metrics to inform decisions, trade-offs, and prioritization in ambiguous, multi-stakeholder environments. 

• Strong written and verbal communication skills, with the ability to translate complex data and technical concepts for diverse audiences. 

• Bachelor’s degree or equivalent related professional experience. 

Preferred Qualifications: 

• Experience with data platform product management, including semantic layers, metric stores, or enterprise data products serving technical users such as engineers, analysts, and data scientists as well as business users. 

• Familiarity with core business metrics infrastructure concepts: metric definition and governance, data lineage, semantic layers, data quality and observability, or experimentation frameworks. 

• Experience driving platform adoption at scale — onboarding new teams, reducing metric fragmentation, and establishing a platform as a system of record across a large organization. 

• Exposure to AI/ML-driven analytics, including familiarity with how LLMs and AI agents consume structured data, semantic layers, or governed metadata. 

• Demonstrated experience taking products from concept to scaled adoption using roadmap planning, backlog management, and tools such as Jira. 

• Experience integrating AI/ML-enabled capabilities into data platform products, including API-based or agent-based integrations.