EVEREVE inspires women to move forward in their fashion so that they feel fully alive. By offering modern, curated trends from 150+ brands, including our own best-selling line—along with warm, genuine advice—we deliver a styling experience made personal. Our 110+ stores, booming e-commerce business, and fast-growing subscription box service, Trendsend, reach over two million customers every year. 

Living our core brand values and treating everyone with HEART (humility, empathy, authenticity, relationships, tenacity) creates a shared purpose and collaborative community—and it's also a key part of our success. Join our team to help shape the future of an ever-growing, ever-evolving brand!

Role Overview

Reports to: Digital Item & AI Lead | Level: 4 | Open Roles: 2  

 This role is onsite at our Edina, MN Headquarters, it is not a remote position.  

The Digital Operations, Item Data Specialist supports the accuracy, completeness, governance, and publication of item data across the digital commerce ecosystem, with an increasing emphasis on preparing product data for AI-enabled experiences, automation, search, content generation, recommendations, and operational decision-making. This role is responsible for product setup, enrichment, descriptions, fit notes, product grouping, brand setup, metafield maintenance, and publishing readiness across categories, ensuring all work follows strong AI protocol, structured data standards, and consistent governance practices. The specialist partners with merchandising, buying, creative, marketing, technology, store operations, and other cross-functional teams to ensure product data is clean, scalable, searchable, machine-readable, operationally reliable, and ready to support both current business needs and future AI-driven workflows. 

Key Responsibilities:

Core Item Data Operations 

• Execute accurate and timely product setup across assigned categories, ensuring item records are complete, consistent, structured, ready for digital publishing and AI-enabled downstream use. 
• Enrich product data, attributes, metafields, product groupings, brand setup, descriptions, and fit notes to support customer experience, search, filtering, merchandising, conversion, automation, and AI readability. 
• Maintain and reconstruct product data in Shopify and related systems as needed to support operational accuracy, scalable catalog management, machine-readable data structures, and governance-aligned AI readiness. 
• Apply established AI protocol and data governance standards when creating, editing, validating, or publishing item data, with attention to consistency, completeness, naming conventions, taxonomy alignment, and structured attribute quality. 
• Support monthly catalog shot list summaries and product availability readiness by coordinating with merchandising, buying, creative, and inventory partners. 
• Identify, investigate, and resolve incomplete, conflicting, outdated, duplicative, or inaccurate product information prior to publication, especially where gaps may limit automation, search performance, personalization, or AI-enabled workflows. 
• Partner cross-functionally to clarify requirements, resolve data issues, improve workflows, and maintain high standards for item data quality, AI readiness, and operational scalability. 

Role Focus Area A: Promotions, Discount Operations, Gift Cards, Store Listings & Store GEO 

• Own enterprise discount code setup, execution, validation, and maintenance in support of promotional campaigns, sale events, and business priorities, while ensuring promotional data follows approved governance and AI-aware data protocols. 
• Support sale setup and scheduling, ensuring promotional pricing, site execution, and related item data are accurate, structured, documented, and aligned to timelines. 
• Create, configure, and maintain gift card setup and related item data requirements in a way that supports clean reporting, consistent customer experiences, and future automation. 
• Maintain store and local listings data, including store GEO details, to support accurate customer-facing location information, local commerce experiences, structured location data, and AI-enabled discovery. 
• Partner with marketing, retail/store operations, digital commerce, and technology teams to troubleshoot promotion, gift card, store listing, and location data issues that may affect customer experience, automation, search, or AI-enabled outputs. 
• Document repeatable processes and quality checks for discount operations, gift card setup, store listing accuracy, and structured data readiness. 

Role Focus Area B: Data Governance, AI Readiness & Item Lifecycle Automation 

• Manage and execute item data governance standards, ensuring attributes, taxonomies, naming conventions, metafields, and product data structures are consistent, scalable, machine-readable, and aligned to approved AI protocol. 
• Lead the documentation and creation of execution guidelines for AI readiness, including standards for clean, normalized, complete, and well-structured item data that can support automated content, search, recommendations, merchandising, personalization, and future AI-enabled workflows. 
• Translate AI governance standards into practical operating procedures, validation checkpoints, data quality rules, and repeatable workflows for item setup, enrichment, maintenance, and lifecycle management. 
• Execute product lifecycle management processes, including automated unpublish rules, seasonal archiving, and item status maintenance, with attention to the data signals required for accurate automation. 
• Manage product availability tracking to monitor inventory, productivity, lifecycle status, and readiness signals that impact what is published online and what is eligible for automated or AI-supported actions. 
• Identify lifecycle bottlenecks and opportunities to reduce manual effort through rules-based workflows, automation, standardized data structures, and governance-driven process improvement. 
• Partner with technology, analytics, merchandising, and operations teams to define data quality requirements, test automated rules, improve governance execution, and ensure AI readiness standards are understood and applied across workflows. 

Qualifications

• 4 years of experience in e-commerce operations, product data, digital merchandising, catalog management, master data management, retail operations, or a related field. 
• Strong attention to detail with the ability to manage high-volume product data accurately, efficiently, and in alignment with defined data governance and AI readiness standards. 
• Experience working with Shopify or similar e-commerce platforms; familiarity with PIM, MDM, ERP, CMS, digital asset, or product data tools preferred. 
• Proficiency with Excel or similar data tools, including sorting, filtering, lookups, bulk data review, data quality checks, and structured data validation. 
• Ability to write clear, customer-facing product descriptions and fit notes while maintaining brand, category, structured data, taxonomy, and AI protocol standards. 
• Understanding of how clean item data, consistent attributes, naming conventions, taxonomy discipline, and normalized content support automation, search, personalization, reporting, and AI-enabled business processes. 
• Strong organizational and prioritization skills, with the ability to manage deadlines, recurring processes, cross-functional dependencies, and governance-driven checkpoints. 
• Comfort working with imperfect or evolving data, identifying root causes, resolving inconsistencies, and improving repeatable processes that strengthen data quality and AI readiness over time. 
• Strong communication skills and ability to partner effectively with merchandising, buying, marketing, creative, technology, stores, and operations teams to drive shared accountability for item data quality and AI-ready execution. 

Preferred Experience

• Experience with product attributes, taxonomies, metafields, product grouping, catalog hierarchy, and product lifecycle rules. 
• Experience supporting promotions, discount code execution, gift card setup, store listings, local listings, or store location data. 
• Understanding of data governance concepts, including data standards, naming conventions, validation rules, completeness, consistency, and audit processes. 
• Familiarity with AI-enabled content, automation, search, personalization, product recommendations, or structured data readiness. 
• Experience in apparel, footwear, lifestyle, home, or specialty retail environments where product descriptions, fit notes, and visual merchandising accuracy are important.