Sr Manager, Product Data Systems

At Home GroupCoppell, TX
4d

About The Position

At Home is seeking a strategic Sr. Manager, Product Data Systems (PIM/PLM) to lead the evolution of the company’s product information, product lifecycle, and purchase order–enabling systems and processes. This role will serve as the enterprise owner for PIM (Product Information Management) and PLM (Product Lifecycle Management), ensuring product data, attributes, specifications, costing, and workflows enable accurate PO creation and business growth across Merchandising, Sourcing, Product Development, Supply Chain, E-commerce, and Marketing. This position will oversee product data governance from concept through go-to-market and into execution, ensuring product setup and attributes fully support SKU creation, PO accuracy, vendor execution, and downstream systems. The Sr. Manager will partner closely with Merchandising, Sourcing, Supply Chain, and IT to ensure clean handoffs from PLM → PIM → ERP → PO execution. This role reports into the Planning & Analytics Team and serves as the company’s expert in PIM/PLM best practices, workflow optimization, product data strategy, and PO-enabling data integrity.

Requirements

  • Expertise in PIM and PLM platforms (Syndigo preferred; PLM experience required).
  • Strong understanding of retail product development, sourcing, and purchase order processes.
  • Ability to influence enterprise-level data governance and workflow changes.
  • Strong product data taxonomy, attribution, and item setup expertise.
  • Excellent cross-functional communication, training, and leadership skills.
  • Skilled in requirements writing, backlog management, and solution delivery.
  • Ability to manage complexity in a fast-paced retail environment.
  • Bachelor’s degree in Business, Information Systems, Merchandising, or related field.
  • 3–5 years of experience working with PIM platforms (Syndigo experience strongly preferred).
  • Retail or consumer product industry experience required.

Responsibilities

  • PLM Ownership & Product Attribution Act as the enterprise expert on PIM functionality, taxonomy, attribution, and enrichment standards.
  • Ensure product attributes support SKU setup, PO creation, packaging, eCommerce content, SEO, and product discovery.
  • Translate business needs into system requirements and user stories; manage the PIM backlog and enhancement roadmap.
  • Maintain consistency between product attributes used for buying, selling, and operational execution.
  • Product Data Integration Across PLM, PIM, ERP & PO Process Align product structures, item setup, and lifecycle statuses across PLM, PIM, ERP, and purchasing systems.
  • Ensure product data required for accurate purchase order creation (costs, pack sizes, MOQ, lead times, vendor details) is governed and consistently maintained.
  • Partner with Merchandising, Sourcing, and Supply Chain to reduce PO errors caused by incomplete or misaligned product data.
  • Lead ongoing harmonization of product data definitions across Merchandising, Sourcing, Supply Chain, and eCommerce .
  • Enterprise Product Data Strategy & Governance Own the enterprise roadmap for PIM and PLM development, integrations, and process improvement.
  • Champion data governance standards across all product-related and PO-related functions.
  • Establish and maintain a single source of truth for product data that feeds PO execution and downstream channels.
  • Define ownership, controls, and accountability for product and PO-enabling data elements.
  • Cross-Functional Leadership & Change Management Facilitate the handoff of product information from PLM → PIM → ERP → PO execution → downstream channels.
  • Train and support business users across Merchandising, Sourcing, Supply Chain, Marketing, Store Ops, Tax, and Compliance.
  • Drive adoption of standardized workflows, data standards, and system enhancements tied to product and PO accuracy.
  • Quality, Testing & Performance Measurement Lead QA and UAT for PIM/PLM releases, integrations, and PO-related enhancements.
  • Measure the impact of product data improvements, including reduced PO errors, improved vendor execution, faster product launches, fewer packaging issues, and improved digital performance.
  • Monitor and enforce data quality standards across all contributors to product and PO data.
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