Senior Product Manager - Digital Data (Hybrid - Seattle)

Nordstrom•Seattle, WA

9d•$142,000 - $220,500•Hybrid

About The Position

Nordstrom is seeking a Senior Product Manager to lead product for digital data in support of its digital business. The role shapes how digital data is collected, managed, and used for decision-making across the company, partnering with business and technology leaders on major priorities. Working with senior leaders and partners in Engineering and Analytics, the Senior Product Manager defines a multi-year vision and translates it into an actionable roadmap. This hybrid role is based in Seattle, Washington. Candidates must be available to work in the Nordstrom corporate headquarters at least four days per week.

Requirements

At least 5 years of product management experience, with meaningful experience in data, business intelligence, analytics or data science, or data platforms.
Experience leading the direction of a data product, platform, or domain and influencing senior leaders on complex data and technical tradeoffs.
Experience with digital analytics platforms such as Google Analytics/GA4, Adobe Analytics, or Quantum Metric, and with how clickstream data is collected and modeled in a cloud warehouse such as BigQuery.
Knowledge of how privacy regulations and device- and browser-level tracking restrictions affect data collection and measurement.
Familiarity with modern cloud data platforms and patterns such as GCP/BigQuery, Looker, dbt, and medallion architecture, sufficient to evaluate tradeoffs.
Experience with data management, including governance, quality monitoring, and self-service enablement.
Strong communication skills, including writing and presenting a compelling investment case and building alignment across a large, matrixed organization.
Bachelor’s degree required.

Nice To Haves

MBA or advanced degree.
Hands-on data modeling experience, such as dimensional modeling or schema design.
Experience scoping or shipping conversational analytics or other AI-powered analytics products built on governed data.
Experience working in an AI-native way, using agents to research, test assumptions, and prototype solutions.

Responsibilities

Define how digital data is governed, unified, and made self-service.
Own the instrumentation and analytics tooling strategy, including build-versus-buy decisions, platform consolidation, and architecture, in partnership with engineering leadership.
Present plans and investment cases to executive leadership, translating technical complexity into business terms.
Set priorities and own the backlog for a dedicated data engineering team, balancing near-term business needs with long-term platform health, and work with Engineering to scope and deliver work.
Improve data quality and trust through shared metric definitions and governance from source systems to reporting.
Build alignment across Product, Engineering, Analytics, and business leaders, including partners in Customer Experience, Merchandising, Marketing, Finance, and Strategy.
Shape how AI changes the way people use digital data, including natural-language querying of metrics and conversational analytics.
Mentor product managers and data consumers on how to find, use, and understand digital data.