Product Data Manager
Listed on 2026-05-31
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IT/Tech
Data Analyst
Product Data Manager
We have a large, complex product catalog and a small, capable e-commerce and IT team. Today, our Data Analyst handles scripted cleanup and pricing updates, our Ecommerce Director manages the website, and our Net Suite Admin builds workflows and manages the ERP. What we are missing is someone who owns the product data itself: the person who defines what clean, complete, and consistent data looks like for our catalog, and who is accountable for getting it there and keeping it there.
This role is the single point of ownership for our entire product data ecosystem. You will be the bridge between our ERP, our website, our manufacturers, and our internal teams, ensuring that the 2.5 million items in our catalog are accurate, well-structured, and optimized for both customer experience and search visibility.
Data Standards & Architecture- Define and enforce the canonical product data model: required fields, naming conventions, variant attribute standards, and category taxonomy across all 300 brands
- Create and maintain the master variant attribute mapping (e.g., consolidating hundreds of inconsistent finish names into a standardized set of canonical values)
- Establish minimum data quality thresholds for product pages to remain published on the website
- Own the translation of business and operational needs into structured data specifications.
- Document requirements, define acceptance criteria, and maintain clear data contracts before any system change or import enters development.
- Design and maintain the product data schema, including table structure, naming conventions, and indexing strategy.
- Write and optimize complex SQL queries.
- Lead the end-to-end data cleanup project across 300,000 parent items and 2.2 million variants, starting with our 50 actively sold brands and expanding to traffic‑only brands
- Audit the existing catalog to quantify data quality issues by type, brand, and severity
- Build and execute normalization processes using a combination of scripting and manual review
- Identify and resolve duplicate items, orphan variants, and incorrect parent‑child relationships
- Cross‑reference Net Suite product records against the live website to identify and fix discrepancies
- Obtain and integrate product data feeds (EDI, API, flat files) from key brand partners such as Brizo, Hansgrohe, and other Tier 1 brands
- Serve as the primary point of contact for manufacturer data inquiries and spec sheet sourcing
- Evaluate and recommend product data syndication tools or PIM platforms to automate ongoing data ingestion
- Own the new product intake process: every item that enters the catalog meets your standards before it goes live
- Build and maintain a data quality dashboard tracking completeness, consistency, and freshness metrics
- Run quarterly catalog audits and report on data health to leadership
- Create and maintain documentation and playbooks so the Data Analyst can execute day‑to‑day maintenance within your framework
- Establish a repeatable testing protocol after every data import, including field‑level validation checks, image integrity verification, pricing accuracy audits, and variant completeness reviews.
- Document pass/fail criteria, maintain a QA checklist, and escalate anomalies before data goes live.
- Work with the Ecommerce Director to ensure product data supports SEO strategy, site search, and filtering
- Work with the Net Suite Admin to ensure data structures, workflows, and integrations support clean data flow between the ERP and the website
- Direct the Data Analyst’s day‑to‑day catalog work, providing standards, priorities, and quality review
- Coordinate with the sales team to understand which product attributes drive customer purchasing decisions and trade partner requirements
- Support the ERP evaluation process by defining product data migration requirements and testing data mapping in any new system
How to apply
Send your resume and a brief note describing the largest product catalog you have managed and what you did to improve its data quality.
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