Data Product Manager Sr

Role Overview & Context

This role is calibrated to the Senior Product Manager (Level 17) anchor within Nordstrom's IC Product Talent Framework. You will own the multi-year vision for store reporting, transforming a fragmented, desktop-bound reporting environment into an intelligent, device-agnostic, and role-based analytics platform.

This is a highly visible role requiring a visionary thinker who can define a 1-3 year strategy, deep-dive into technical dashboard configurations, work across matrixed domains, and comfortably present business-impact narratives to VPs and executive leadership.

Logistics & Work Arrangement

• Position Type: 3-Month Contract
• Compensation: ~$80.99 per hour on W2
• Location: Onsite in Seattle (4 days per week, any 4 days; 1 day remote)
• Schedule: 9:00 AM - 5:00 PM (8 hours/day). Overtime could occasionally arise based on business needs.
• Potential: High potential to extend or convert to full-time based on business needs.
• Tech Stack & Tools: MacBook environment | Looker, Tableau, Claude, Microsoft Suite, GCP / BigQuery.

Key Responsibilities

Product Strategy & Roadmap

• Own the Multi-Year Vision: Drive the evolution of store reporting from today's reliable Looker reporting toward proactive, intelligent, "next-best-action" capabilities.
• Modernize the Experience: Shift the current fragmented, desktop-heavy reporting ecosystem into intelligent, device-agnostic, and role-based reporting delivered in prioritized increments.
• Data Governance: Maintain momentum on metric definitions and certification workflows. Serve as the core product voice in architectural and data governance discussions.

Delivery & Execution

• Backlog Management: Independently write comprehensive user stories and acceptance criteria across complex domain dependencies. Maintain a highly refined backlog sequenced by user impact, business value, and engineering effort.
• Risk & Dependency Mitigation: Proactively identify and manage cross-team dependencies and sequencing tradeoffs. Document and escalate recommendations to leadership when appropriate.
• Data-Driven Iteration: Define and track success metrics for shipped features. Leverage telemetry and user feedback to drive root-cause analysis and continuous roadmap adjustments.

User Research & Stakeholder Alignment

• User Discovery: Lead independent discovery with the full store population (store leaders, department managers, sellers), synthesizing findings into clear opportunity statements.
• Matrix Alignment: Drive alignment across a complex matrix including Insights Delivery Engineering, the CIA/data team, business stakeholders, store operations, and Director/VP leadership.
• Uplevel Communication: Own communications up and down the pyramid, translating complex technical tradeoffs for engineering and framing high-level business impact narratives for VPs.

Senior PM (Level 17) Core Expectations

• Collaboration & Influence: Orchestrate planning across the store reporting domain and dependencies. Influence roadmaps and ensure seamless execution without relying on manager direction.
• Definition & Decomposition: Remove product ambiguity independently. Align stakeholders on scope and boundaries while bringing sufficient technical depth to enable extensible design decisions.
• Evangelize Test-and-Learn: Demonstrate product-market fit through robust measurement. Proactively make evidence-based roadmap adjustments without management prompting.

Role Requirements

Required Qualifications

• Experience: 5+ years of end-to-end Product Management experience, with a proven track record of owning a product domain at the Senior PM level.
• BI Platforms: Deep expertise with enterprise BI and reporting platforms-specifically Looker -and how they integrate with modern cloud data ecosystems ( GCP/BigQuery strongly preferred).
• Migrations: Hands-on experience driving platform migration or consolidation efforts, including legacy deprecation, user change management, and stakeholder alignment.
• Data Governance: Strong foundational knowledge of metric certification, semantic layers, data ownership models, and the structural distinction between data producers and consumers.
• Technical Depth: Fluency in data engineering and analytics fundamentals, SQL, data warehousing, and pipeline concepts necessary to engage credibly with engineering on architectural tradeoffs.
• Communication: Exceptional written and verbal communication skills; ability to author crisp artifacts tailored for both engineering teams and executive leadership.

Preferred Qualifications

• Experience with conversational analytics, agentic AI, or LLM-powered product development.
• Familiarity with Nordstrom's store operations context, store leader personas, or retail workforce management.

Interview Process

1. Initial Screen: Hiring Manager Interview
2. The Loop (3-Person Panel):
   • Analytics Interview
   • Strategy Interview
   • Ways of Working Interview