✦ Luna Orbit — Executive & General Management

Director of Engineering, Technology Merch Planning - Hybrid - Seattle

at Nordstrom

📍 Seattle, WA Hybrid 💰 $200K – $332K USD / year Posted March 13, 2026
Salary $200K – $332K USD / year
Type Full-Time
Experience lead
Exp. Years 10+ years
Education Not specified
Category Executive & General Management

This leadership role involves overseeing the development and strategy of merchandising technology solutions, leveraging ML and analytics to optimize business outcomes.

  • Oversee merchandising tech strategy
  • Lead engineering teams
  • Drive ML and analytics integration
  • Develop technical roadmaps
  • Collaborate with data science

Focuses on ML, data science, analytics, and application development within the retail merchandising domain, requiring strategic leadership and technical expertise.

The ideal candidate is a senior leader with over 10 years in engineering, specializing in ML, data science, and retail technology. They have proven leadership skills and experience developing strategic technical roadmaps for merchandising solutions.

Experience leading engineering teamsStrong background in ML and data scienceExperience with merchandising technologyTechnical strategy development
Experience with AI applicationsKnowledge of retail industrySustainable technology practices
ML frameworksAnalytics toolsApplication development platformsData science tools
Machine LearningMLData ScienceMerchandising TechnologyAnalyticsApplication DevelopmentTechnical StrategyLeadership
Machine LearningMLData ScienceSoftware DevelopmentMerchandising TechnologyAnalyticsApplication DevelopmentTechnical StrategyLeadership
leadershipstrategic thinkingcollaborationcommunicationproblem-solving
Industry Retail / E-commerce / Technology
Job Function Lead the engineering and strategic development of ML-driven merchandising solutions
Machine LearningMLData ScienceMerchandising TechnologyAnalyticsApplication DevelopmentTechnical StrategyLeadership

Less than 10 years of leadership experience, No background in ML or data science, Lack of experience with merchandising technology

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