Technical Product Owner – PIM & Data Architecture

International Motors, LLC•Lisle, IL

22h

About The Position

We are seeking a Technical Product Owner – PIM & Data Architecture to own and scale the product data foundation that powers our digital commerce ecosystem. This role is responsible for defining, governing, and continuously improving the “Product Truth”—from complex multi-source ingestion through enrichment and publication across storefronts, dealer tools, and downstream platforms. You will sit at the intersection of product management, data architecture, and engineering, translating complex data and catalog challenges into scalable, high-quality solutions that directly impact conversion, fitment confidence, and customer experience. This is a hands-on role designed for someone who thrives in highly technical environments and can lead through influence, clarity, and data-driven decision-making.

Requirements

Bachelor's degree and at least 5 years of technical project/program management experience
At least 1 years of lead experience
OR
Master's degree and at least 3 years of technical project/program management experience
At least 1 years of lead experience
OR
At least 8 years of technical project/program management experience
At least 1 years of lead experience
Qualified candidates, excluding current employees, must be legally authorized on an unrestricted basis (US Citizen, Legal Permanent Resident, Refugee or Asylee) to be employed in the United States. We do not anticipate providing employment related work sponsorship for this position (e.g., H-1B status)
5+ years as a Technical Product Owner, Data Product Manager, Data Architect, or Systems Analyst in a PIM, MDM, or complex catalog environment.
Proven experience designing and governing large-scale product data models (100k+ SKUs).
Hands-on experience with PIM platforms such as Syndigo, Akeneo, Salsify, or similar.
Strong background working in Agile environments with highly technical engineering teams.
Deep understanding of JSON schemas, EAV models, APIs (REST/GraphQL), SQL, and data validation patterns.
Experience integrating PIM with eCommerce platforms, ERPs, fitment systems, and DAMs.
Familiarity with automotive, aftermarket, industrial, or B2B product catalogs is strongly preferred.
Practical experience applying AI/ML or LLM-based tools to data enrichment, quality, or automation use cases.

Responsibilities

Own the Product Data Strategy & “Golden Record”
Define and govern the global product taxonomy, category structures, and technical attribute standards within our PIM ecosystem (Syndigo or equivalent).
Design and evolve the PIM data model, including inheritance, multi-level taxonomies, and EAV-based attributes.
Establish and enforce Golden Record standards, schemas, and validation rules to ensure accuracy, consistency, and completeness across all SKUs.
Serve as the final decision-maker for schema changes, attribute definitions, and data governance standards.
Drive End-to-End Data Orchestration
Lead the technical strategy for supplier and OEM data onboarding, including mapping logic, transformations, and exception handling.
Partner with engineering teams to translate complex data requirements into clear user stories, acceptance criteria, and backlog priorities.
Collaborate with Commerce, Fitment, Storefront, and DAM teams to ensure seamless data flow across the ecosystem.
Ensure PIM, DAM, ERP, and eCommerce platforms integrate via API-first, scalable architectures.
Leverage AI to Scale Data Quality & Enrichment
Apply AI and rule-based approaches to automated categorization, attribute mapping, and schema validation.
Use AI-driven auditing to detect data gaps, inconsistencies, duplicates, and anomalies, routing exceptions through human-in-the-loop workflows.
Leverage LLMs to generate SEO-optimized product descriptions and technical summaries at scale, with governance and quality controls.
Continuously refine AI outputs through feedback loops, confidence scoring, and impact measurement.
Ensure Cross-Reference & Related-Part Integrity
Govern OEM and aftermarket interchange and cross-reference mappings, including supersessions and alternates.
Identify and resolve duplicate and near-duplicate parts using similarity matching and survivorship rules.
Build and maintain a related-part relationship graph (substitutes, accessories, kits, required/compatible items).
Validate consistency between technical attributes and vehicle/application fitment logic, proactively flagging conflicts.
Ensure all enrichments and relationships are traceable to source with audit history and confidence indicators.