Process Engineer, Energy Warehouse Operations

2 Hours ago • 3 Years + • Logistics

About the job

Job Description

Tesla seeks a Process Engineer for Energy Warehouse Operations to design and implement innovative processes and systems. This role involves optimizing warehouse operations across the APAC region (Australia, New Zealand, Japan, Korea, etc.), requiring 20% travel. Responsibilities include designing material flow processes, collaborating with operations teams, developing hardware/software requirements, conducting ROI analyses, resolving WMS issues, analyzing data, creating process maps, and implementing lean principles. The ideal candidate will possess a Bachelor's or Master's degree in a related field and 3+ years of relevant experience.
Must have:
  • Industrial Engineering Degree
  • 3+ years warehouse experience
  • WMS, SQL, Power BI knowledge
  • Lean principles implementation
  • Data analysis & problem-solving
  • Cross-functional collaboration
Good to have:
  • AutoCAD proficiency
  • Master's Degree
What to Expect

Tesla is looking for a highly motivated and results-driven Process Engineer to design and implement innovative processes and systems for our Energy Hub Operations. This role is crucial to transforming Tesla's supply chain, optimizing warehouse operations, and driving continuous improvement across our global network. 

Working in a fast-paced, dynamic environment, you will collaborate extensively with internal and external teams, applying your expertise in industrial engineering, lean principles, and data analytics to optimize material flow, reduce inefficiencies, and achieve Tesla’s ambitious goals.

This position has an APAC wide scope, with an expectation of 20% travel across the region to warehouses in Australia, New Zealand, Japan, Korea, and several other countries. 

What You’ll Do
  • Design and refine material flow processes and standards, focusing on cost efficiency, throughput optimization, and accuracy improvement.
  • Collaborate with Warehouse Operations teams to identify improvement opportunities, lead concept development, prototype solutions, and implement designs in operations.
  • Develop hardware (MHE), software (WMS), and KPI requirements, conduct ROI analyses, and implement process upgrades.
  • Work cross-functionally with teams including IT developers, supply chain automation, material planning, infrastructure, and logistics to ensure seamless integration of systems and processes.
  • Lead the resolution of warehouse management system (WMS) issues, identify root causes, and implement long-term solutions in collaboration with developers.
  • Collect and analyze data (e.g., cycle time studies, workflow mapping) to optimize operational processes and create detailed reports for decision-making.
  • Create layouts, standardized work documents, and process maps for workstation rebalancing and process optimization.
  • Facilitate training and team development to support system and process improvements, aiming to enhance accuracy and efficiency.
  • Implement lean principles such as 5S, Just-in-Time (JIT), and Continuous Improvement to drive operational excellence.
What You’ll Bring
  • Bachelor’s or Master’s Degree in Industrial Engineering, Operations Research, Systems Engineering, Supply Chain Management, or a related field.
  • 3+ years of experience in manufacturing, logistics, or warehousing environments, with hands-on exposure to materials management and process improvement.
  • Advanced proficiency with Microsoft Office Suite (Excel, PowerPoint, Word).
  • Strong working knowledge of Warehouse Management Systems (WMS), SQL, Power BI, Tableau, and AutoCAD.
  • Familiarity with Lean concepts such as Takt Time, Cycle Time, 5S, and work measurement principles.
  • Proven ability to manage competing demands and meet tight deadlines in a fast-paced environment.
  • Strong analytical skills with a data-driven approach to problem-solving.
  • Excellent communication and interpersonal skills, with a talent for building collaborative relationships across teams.
  • Ability to thrive in unstructured environments with incomplete or ambiguous data.
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