Lead the end-to-end configuration of PIM features, including attributes, complex taxonomies, multi-channel hierarchies, and role-based access controls.
Develop and manage robust Data Models to support diverse retail requirements (e.g., eCommerce, brick-and-mortar, and mobile).
Engineer and optimize automated workflows for product data enrichment, multi-stage approvals, and cross-platform publishing.
Partner with technical leads to build and validate preview capabilities within pre-production staging environments.
Architect and maintain API connections , data pipelines, and scripts (Python/JavaScript) to ensure high-fidelity data flow.
Lead technical integrations for specialized third-party vendors, including translation services ( Writer AI ) and downstream attribution software.
Pioneer the implementation of PIM AI capabilities , focusing on automated product attribution via PDF tech-pack extraction and image recognition technologies.
Oversee large-scale data migrations in collaboration with vendors and internal stakeholders to ensure 100% data accuracy and completeness.
Monitor platform performance and proactively refine configurations to enhance system automation and usability.
Author and maintain comprehensive technical documentation, including integration maps, workflow diagrams, and configuration guides.
Stay abreast of vendor-specific updates and PIM best practices to maximize platform ROI.
Provide ongoing technical mentorship and support to internal IT teams and platform super-users.
Experience: 5+ years of technical experience implementing enterprise PIM platforms (e.g., Salsify, Akeneo, Inriver, or Informatica ).
Data Mastery: Deep expertise in data modeling, attribute management, and product governance frameworks.
Technical Stack: Proficiency in APIs (REST/SOAP) , scripting languages, and data formats ( JSON, XML, CSV ).
ETL & Middleware: Hands-on experience with integration tools such as MuleSoft, Boomi, or Data Fusion .
Systems Interoperability: Strong understanding of how PIM interacts with ERP, PLM, DAM, and CMS platforms.
Vertical experience in Retail, eCommerce, or Consumer Goods .
Familiarity with Agile/DevOps methodologies for managing system releases and enhancements.
Experience in automated data enrichment and AI-driven product categorization.
Successful deployment of a scalable system configuration aligned with core business requirements.
Seamless establishment of data pipelines between the PIM and all downstream eCommerce systems.
Implementation of automated workflows resulting in measurable improvements to data enrichment speed.
High data integrity and minimal reconciliation issues post-migration.

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MDA Edge

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MDA Edge