Industrial Engineer

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The Industrial Engineer is responsible for designing, optimizing, and governing material flow throughout the entire value stream, from the supply base through manufacturing and ultimately to the operator workstation. This role owns the Digital Plan for Every Part (PFEP), leveraging advanced analytics, artificial intelligence (AI), simulation modeling, and Factory of the Future technologies to create a highly efficient, data-driven material delivery system. The position serves as the strategic leader for material conveyance, inventory optimization, automation integration, and future-state manufacturing logistics.

·       Develop, maintain, and govern a comprehensive Digital PFEP database for all production and indirect materials.

·       Ensure accurate part attributes including dimensions, packaging, consumption rates, storage locations, transportation methods, and delivery frequencies.

·       Establish data governance standards to maintain PFEP accuracy and integrity.

·       Collaborate with Supply Chain, Manufacturing Engineering, Launch, Purchasing, and Operations teams to ensure alignment.

·       Drive PFEP integration with ERP, MES, WMS, and automated material handling systems.

·       Analyze end-to-end material movement from supplier docks through production consumption.

·       Develop optimal replenishment strategies including JIT, sequenced delivery, line-side presentation, and supermarket systems.

·       Establish standardized material presentation methods to improve ergonomics and productivity.

·       Reduce touches, travel distance, inventory levels, and material handling waste.

·       Lead Value Stream Mapping and Material Flow Mapping initiatives.

·       Utilize AI tools to analyze material consumption patterns and logistics performance.

·       Develop predictive models for inventory shortages, line disruptions, container utilization, and supplier performance.

·       Use machine learning algorithms to identify inefficiencies and optimization opportunities.

·       Create automated dashboards and decision-support tools for operations teams.

·       Partner with Digital Manufacturing and IT teams on AI roadmap development.

·       Build simulation models of material movement using Digital Twin technologies.

·       Model AMR routes, tugger paths, supermarket sizing, storage requirements, and conveyance systems.

·       Simulate production changes, volume increases, labor reductions, and automation investments.

·       Evaluate scenarios for new product launches and facility expansions.

·       Use simulation outputs to support capital expenditure decisions and ROI analysis.

·       Develop strategies for AMRs, AGVs, ASRS, automated conveyors, smart carts, autonomous forklifts, and future logistics technologies.

·       Evaluate automation opportunities that improve safety, quality, and productivity.

·       Support implementation of automated replenishment and material tracking systems.

·       Ensure integration between physical automation systems and digital planning tools.

·       Drive standardization of automated logistics processes across the facility.

·       Research emerging technologies and evaluate applicability within manufacturing operations.

·       Develop multi-year roadmaps for logistics automation and Industry 4.0 implementation.

·       Identify opportunities for real-time data collection and autonomous decision-making systems.

·       Integrate IoT, AI, Digital Twins, and predictive analytics into daily operations.

·       Establish future-state material handling standards to support increasing automation.

·       Determine optimal inventory levels throughout the production process.

·       Establish storage strategies for supermarkets, warehouses, ASRS systems, and point-of-use locations.

·       Analyze container density, rack utilization, and warehouse capacities.

·       Support supply chain risk mitigation planning.

·       Drive inventory reduction initiatives while maintaining delivery performance.

·       Lead material flow improvements for new product launches and plant expansions.

·       Support manufacturing engineering, operations, maintenance, and supply chain teams.

·       Present business cases and recommendations to leadership teams.

·       Drive continuous improvement initiatives utilizing Lean Manufacturing principles.

·       Manage logistics-related capital and continuous improvement projects.

• Bachelor's degree in Supply Chain, Industrial Engineering, Manufacturing Engineering, Logistics, Operations Management, Data Analytics, or related field; or an equivalent combination of education and experience preferred.

• 5+ years in manufacturing logistics, material flow, industrial engineering, supply chain, or automation.

• Experience managing PFEP systems.

• Experience with automation technologies including AMRs, AGVs, ASRS, and smart manufacturing systems.

• Experience with simulation software and analytical tools.

• Experience within automotive, aerospace, or advanced manufacturing environments preferred.

• Digital PFEP Development

• Material Flow Engineering

• AI & Machine Learning Applications

• Simulation Modeling

• Digital Twin Technology

• Industry 4.0 Systems

• Warehouse Management Systems

• ERP Systems (SAP, Oracle, QAD)

• Power BI, Tableau, SQL

• Lean Manufacturing

• Value Stream Mapping

At Magna, we believe that a diverse workforce is critical to our success. That’s why we are proud to be an equal opportunity employer. We hire on the basis of experience and qualifications, and in consideration of job requirements, regardless of, in particular, color, ancestry, religion, gender, origin, sexual orientation, age, citizenship, marital status, disability or gender identity. Magna takes the privacy of your personal information seriously. We discourage you from sending applications via email or traditional mail to comply with GDPR requirements and your local Data Privacy Law.

As part of our commitment to a fair, consistent, and efficient recruitment process, we may use artificial intelligence (AI) tools to assist in the initial screening of applications submitted through our Workday system. These tools help identify qualifications and experience that align with the role requirements. Please note that AI is used solely to support our recruiters. Final decisions are always made by the hiring manager and the hiring team. Importantly, no applicant data is shared externally through these AI tools. All information remains securely within our systems and is handled in accordance with our privacy and data protection policies.

If you have any questions or concerns about this process, feel free to contact our Talent Attraction team.