The Logistics Engineer is a key member of the logistics warehouse team and is responsible for driving world class performance in operations, customer service, and productivity within our distribution centers. This role leads to continuous improvement using the Schneider Performance System (SPS), with a strong focus on warehouse flow optimization, warehouse design, and governance of process controls enabled by Industry 4.0 (4IR) tools and technologies. The Logistics Engineer combines core industrial engineering skills with advanced data analytics, machine learning, and AI to understand how the warehouse actually operates, identify constraints, and implement robust, data driven solutions. The successful candidate is a hands on leader and influencer who can operate comfortably on the warehouse floor and in digital tools, translating complex analysis into practical actions. What will you do?

• Design, analyze, and continuously improve warehouse flow processes (inbound, storage, picking, packing, outbound) to reduce waste, increase throughput, and improve service levels.
• Lead warehouse layout and design optimization using IE tools (time studies, capacity models, simulations) and CAD, supported by data driven scenario modeling.
• Strengthen and standardize governance of process controls (standard work, work instructions, Time Standards, KPIs, control plans) to ensure stable, repeatable operations.
• Use Advanced Data Analytics, ML, and AI tools to: o Detect bottlenecks and inefficiencies in real time. o Analyze demand, workload, and capacity requirements. o Optimize labor planning, slotting, routing, and equipment utilization.
• Conduct SMB2 time studies or utilize MTM or video based time measurement software to create and maintain accurate time standards; use these to drive engineered labor standards and productivity improvements.
• Build and maintain digital dashboards and monitoring tools (e.g., in Tableau, Power BI, or similar) that provide visibility to performance, process adherence, and exceptions for leaders and operators.
• Design and implement automated data pipelines and reporting to support daily management, problem solving, and governance of key warehouse processes.
• Identify ergonomic and safety concerns using data (near miss trends, exposure data, motion analysis) and collaborate with EHS and operations to design and implement preventive solutions.
• Apply Lean and Six Sigma methodologies, SPS tools, PFMEA, Control Plans, 8D, Fishbone diagrams, and root cause analysis, enhanced by data science and advanced analytics.
• Partner with IT, Data, and performance / smart factory teams to leverage 4IR solutions such as IoT sensors, WMS/WCS data, digital twins, and predictive models in daily operations.
• Develop business cases and cost/benefit analyses for process and capital improvements, including data driven justification for automation, technology, and layout changes.
• Ensure that new processes and tools are.

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