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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # PIM/DAM Business Analyst | Agentic Commerce - **Company:** Accenture - **Location:** Milwaukee, WI, United States - **Salary:** $63,800.0 - $196,000.0 - **Contract:** Permanent contract - **Skills:** Data Analysis, Data Migration, Systems Development Life Cycle, Requirements Traceability, Test Case, Large Language Models, Virtual Agents, Google Shopping - **Published:** May 19, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=509f7a1e21dd3adc ## About the Role * 3+ years of experience in business analysis fundamentals with understanding of PIM concepts, product data structures, and content lifecycles * 2+ years of full lifecycle implementation experience using various SDLC methodologies * 1+ year Exposure to PIM platforms such as Salsify, Akeneo, Syndigo, inRiver, Stibo STEP, or Informatica P360 (hands-on or project-based) Bonus points if: * Solid understanding of AEO and GEO strategies and how to adapt product data for LLM's * Familiarity with attributes, hierarchies, variants, and localization * Knowledge of GDSN concepts, Digital Shelf Analytics, Enhanced Content, Retailer schemas & validation rules * Experience with multi-lingual and multi-market implementations * Experience with GenAI or Agentic AI integration within PIM platforms * Experience with AEO, GEO #LI-NAFY25 ## Description The PIM Business Analyst supports the delivery of PIM solutions by eliciting, documenting, and validating requirements related to product data, content, and business processes. This role focuses on detailed analysis, traceability, and clarity, ensuring that business needs are well understood and accurately reflected in the solution design. The Business Analyst works under the guidance of the PIM Functional Lead and in close collaboration with technical teams to translate requirements into actionable user stories, acceptance criteria, and functional documentation. This role is critical to maintaining alignment between stakeholders, delivery teams, and the final implemented solution. The work: * Elicit and document business requirements through interviews, workshops, and process reviews * Analyze current-state product data flows and identify gaps, inefficiencies, and improvement opportunities * Document functional requirements, use cases, and acceptance criteria * Support product data attribute definition, field mapping, and taxonomy documentation * Create and maintain user stories and backlog artifacts in collaboration with delivery teams * Support data migration and integration analysis by documenting source-to-target requirements * Assist with UAT planning, test case development, and defect triage * Ensure requirements traceability from discovery through delivery and validation * Support change management and training documentation efforts * Drive AEO and GEO strategies for clients using PIM data for LLM syndication * Stay up to date on industry trends related to Agentic Commerce and leverage of GenAI and Agentic solutions to automate the product content supply chain ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Empowering Retail Through Applied Machine Learning](https://www.wearedevelopers.com/videos/976-empowering-retail-through-applied-machine-learning) - [AIQSpecFlow: Improves and automates your agile process of specification and creation of testcases.](https://www.wearedevelopers.com/videos/100084-aiqspecflow-improves-and-automates-your-agile-process-of-specification-and-creation-of-testcases) - [Swapping a Data Warehouse at Runtime: Zero-Downtime Migration Without Changing a Single Client](https://www.wearedevelopers.com/videos/100311-swapping-a-data-warehouse-at-runtime-zero-downtime-migration-without-changing-a-single-client) - [AI as a Test Designer: Transforming Experience into Automated Testing](https://www.wearedevelopers.com/videos/1984-ai-as-a-test-designer-transforming-experience-into-automated-testing) - [Data Science on Software Data](https://www.wearedevelopers.com/videos/162-data-science-on-software-data) ## Related Articles - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [The Biggest German Tech Companies](https://www.wearedevelopers.com/magazine/424-the-biggest-german-tech-companies) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering)