Product Manager II, Data Platform

Expedia Group•Seattle, WA

1d•$112,000 - $179,000•Hybrid

About The Position

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.

Requirements

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.

Nice To Haves

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.

Responsibilities

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.