Product Manager 2 - Insights Delivery: Merchandising (Hybrid - Seattle)

Nordstrom•Seattle, WA

8h•Hybrid

About The Position

The Product Manager 2, Insights Delivery Merchandising is a key contributor to Nordstrom’s Product Management team, supporting the reliability and evolution of the data and reporting platform that Merchandising relies on to make decisions. Product Management is responsible for ensuring we build the right products and features for our customers and business. To accomplish that, product managers help plan the product roadmap, support product discovery initiatives, and assist in measuring the results of the feature portfolio in production, while maintaining clear communication with stakeholders. The Platform, AI, and Data (PAID) team is looking for a product manager who can own the Insights Delivery Merchandising roadmap including spanning platform migrations, new data onboarding, and business intelligence support. This individual should be comfortable getting into the technical weeds of merchandising data and building trust with both engineering and business stakeholders, including merchandising leadership.

Requirements

Proven ability to prioritize features based on customer impact and data-driven insights
Experience breaking down roadmaps into releasable features, writing user stories with acceptance criteria, and managing product backlogs
Demonstrated ability to balance scope, resources, and timelines to maximize product development impact
Ability to foster collaboration across business, technology, UX, and data science teams to drive product delivery
Ability to conduct customer research and market analysis to identify trends and opportunities in data democratization, AI-powered innovation, and big data industries
A “test and learn” mindset, using measurement plans and telemetry to validate hypotheses and iterate on product decisions based on learnings
Strong understanding of data engineering concepts, including data warehousing, data management, and data analysis
Proficiency in SQL and analytical thinking, with exposure to machine learning concepts and applications
Familiarity with cloud data platforms and services such as: Google Cloud Platform (GCP): BigQuery, Looker, Dataplex, Dataproc, Pub/Sub Or equivalent platforms: Databricks, AWS (S3, Data Lake, Redshift), Microsoft Fabric
Ability to analyze data processes and identify opportunities for improved accessibility and AI-driven enhancements
Technical aptitude with a willingness to learn software development principles, A/B testing methodologies, and the integration of machine learning models into data product workflows
2+ years of experience in product management, technology, or a related field
Bachelor’s degree in engineering, Information Technology, Computer Science, Data Science, or equivalent experience
Strong interpersonal, oral, and written communication skills with the ability to build relationships with technical and non-technical stakeholders
Experience coordinating cross-functional efforts and influencing stakeholders to align on product strategy and roadmap decisions

Nice To Haves

Enthusiasm and eagerness: You are passionate about product management and data reliability, with a genuine interest in how governed data enables better business decisions.
Natural curiosity: You ask thoughtful questions and seek to understand data pipelines, business data-submission processes, and emerging AI-enabled data tooling. You are committed to continuous learning.
Problem-solving mindset: You show initiative in tackling data quality issues, seek to understand root causes fully, and explore how tooling or process changes might prevent recurrence. You’re not afraid to ask for help when needed.
Adaptability: You thrive in dynamic environments, switching between incident response, migration work, and roadmap planning as needed.
Willingness to handle ambiguity: You thrive in situations where data ownership boundaries are still being defined, and use data and collaboration to drive clarity.
Interest in industry trends: You stay informed on developments in retail data platforms, cloud architecture, and AI-enabled data quality tooling, sharing ideas and contributing to roadmap discussions with stakeholders.

Responsibilities

Build strong cross-functional relationships across business, technology, UX, and data science teams.
Evangelize the product vision and influence strategic roadmap decisions within the data and AI platform domain.
Actively contribute to planning sessions and coordinate collaborative efforts to deliver impactful features.
Conduct customer research and share findings to develop a deep understanding of the product and customer.
Stay informed on market trends, competitor products, and emerging AI-powered technologies, integrating insights into product strategies.
Break down roadmaps into releasable features and own the prioritization and sequencing of features to best support strategic goals.
Write complete user stories and acceptance criteria within the data platform domain, including features leveraging AI and machine learning models.
Collaborate with engineering to balance customer value with technical effort and complexity.
Develop measurement plans and exercise a “test and learn” mentality, iterating on product decisions based on data and learnings.
Partner with engineering, UX, and data analytics teams to deliver business value through data platform features.
Design testing strategies and measure the impact of AI-driven insights and automation.
Integrate repeatable measurement into decision-making processes to drive roadmap adjustments and ensure outcomes align with business priorities.
Prioritize the product roadmap to optimize impact and balance deliverables across multiple stakeholders.
Develop detailed feature plans, accounting for technical and operational constraints while ensuring iterative value delivery.
Coordinate across squads and functional areas to ensure proper process support for the product.
Contribute to the product vision, articulating its purpose and aligning it with Nordstrom’s strategic vision.
Shape the approach to deliver on the product vision, connecting short-term plans to success metrics and product value.
Evangelize the vision with the squad and key stakeholders, driving alignment on strategy and execution.