Product Manager Technical - Manufacturing Intelligence & Digital Thread, Amazon Robotics

Requirements

• 3+ years of data engineering, database engineering, business intelligence or business analytics experience
• Experience defining roadmap strategy and prioritizing deliverables for your team products
• Experience defining requirements and using data and metrics to draw business insights
• Knowledge of data engineering pipelines, cloud solutions, ETL management, databases, visualizations and analytical platforms
• Knowledge of ERP systems (e.g. SAP, ORACLE, Coupa) in large organizations
• Experience in complex work environments, including (but not limited to robotics, automation, diagnostic and test equipment)
• Experience with Tableau, Python, SQB, Quicksight, Cognos or or other BI packages
• Experience with AI/ML technologies
• Familiarity with Amazon's operating model (OP1/OP2, Working Backwards, PR/FAQ)
• Experience with data governance, semantic layers, or knowledge graphs
• Understanding of digital thread or Industry 4.0 concepts
• Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
• USA, MA, North Reading - 129,200.00 - 174,800.00 USD annually
• USA, MA, Westboro - 129,200.00 - 174,800.00 USD annually
• Partner with program teams, quality engineers, and manufacturing operations to define data product requirements
• Collaborate with enterprise system owners on integration needs and data structure initiatives
• Manage stakeholder expectations and communicate progress across RMTO leadership
• Data Product Development
• Drive development of production intelligence dashboards, semantic layers, and enterprise data catalogs
• Define user experience for self-service reporting and natural language query capabilities
• Oversee knowledge graph design and AI assistant persona development for planning and operations teams
• Technical Leadership & Cross-Functional Coordination
• Work with BIE team to ensure technical feasibility and optimal implementation approaches
• Coordinate with IT and data engineering teams on infrastructure requirements and scaling
• Support change management and user adoption across manufacturing sites
• Basic Qualifications:

Additional Information

Lead the product strategy and execution for RMTO's unified manufacturing intelligence platform, transforming fragmented operational data into actionable insights that accelerate product development and manufacturing operations. Own the roadmap for business intelligence, self-service analytics, and AI-powered decision support tools that enable real-time visibility into production, quality, and supply chain performance across 15+ NPI programs. Partner with Business Intelligence Engineers, operations teams, and enterprise system owners to deliver data products that connect Teamcenter PLM, Kinaxis SCP, Tulip MES, and SAP ERP into a unified digital thread. Key job responsibilities Product Strategy & Roadmap - Define and execute the manufacturing intelligence roadmap; prioritize features based on business impact and customer needs - Build unified digital thread connecting enterprise data systems; standardize performance visibility across all platforms - Establish success metrics for reporting efficiency, data latency reduction, and time-to-insight improvements Voice of the Customer & Requirements - Partner with program teams, quality engineers, and manufacturing operations to define data product requirements - Collaborate with enterprise system owners on integration needs and data structure initiatives - Manage stakeholder expectations and communicate progress across RMTO leadership Data Product Development - Drive development of production intelligence dashboards, semantic layers, and enterprise data catalogs - Define user experience for self-service reporting and natural language query capabilities - Oversee knowledge graph design and AI assistant persona development for planning and operations teams Technical Leadership & Cross-Functional Coordination - Work with BIE team to ensure technical feasibility and optimal implementation approaches - Coordinate with IT and data engineering teams on infrastructure requirements and scaling - Support change management and user adoption across manufacturing sites

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