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Drive innovation in collectibles manufacturing by researching new materials, equipment, and processes to enhance product performance, cost, and fan experience for sports memorabilia and trading cards.
About Us Fanatics is building a leading global digital sports platform. We ignite the passions of global sports fans and maximize the presence and reach for our hundreds of sports partners globally by offering products…
Reviews pre-production text and art files for trading card products, ensuring accuracy, design consistency, and compliance with licensor standards in a fast-paced sports collectibles environment.
Business Systems Analyst at Fanatics Collectibles bridges business needs with technology solutions, focusing on finance, supply chain, and ERP systems like MS D365 or Oracle Fusion to improve processes and implement new platforms.
Leads the product strategy and roadmap for Fanatics Live, a livestream commerce platform for sports collectibles, focusing on platform stability, scalability, and international expansion using technologies like livestreaming, payments, and marketplace systems.
Designs and optimizes manufacturing processes for collectibles production, applying Lean/Six Sigma methods to boost efficiency and quality while reducing waste.
Builds and optimizes full-stack features to drive user growth, engagement, and experimentation across Fanatics' collectibles and sports platforms using modern web technologies.
Builds and maintains the Android app for Fanatics Live, a livestream commerce platform for sports collectibles, using Kotlin, Jetpack Compose, and modern Android architecture.
The Corporate Network Engineer will design, implement, and maintain the network infrastructure for the company's Portland headquarters and lab facilities. This role involves hands-on work with wired and wireless networks, network security, and automation to support the company's renewable energy and ocean-based computing initiatives.
Designs and maintains automated regression testing for a live-service Unity mobile game, using Python, Pytest, and AI tools to reduce manual testing and improve CI/CD pipeline reliability.
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