Associate Manager, Parts Quality (m/w/d) - Gigafactory Berlin-Brandenburg

  • Tesla
  • Berlin, Germany
  • 19/07/2021
Full time Data Science Data Analytics Big Data Data Management Statistics

Job Description

This position is an integral part of the Supply Chain Operations organization and will be responsible for managing the development, selection, implementation & optimization of a growing team of Supplier Quality Engineers, Quality Technicians, Quality Supervisors, Leads, Inspectors & Associates. The successful candidate will ensure all products and processes meet customer and company requirements. He/she will be responsible for quality processes that ensure sort, rework, rejected material disposition and material returns are executed efficiently. The Manager will be responsible for reporting on open rework/sort activity and working closely with the Quality and Supplier Industrialization Engineers to bring timely closure to them.


  • Work closely with Production, Quality, Supplier Industrialization, Design and Suppliers to assure confirming material is delivered to the line and non-conforming material is properly dispositioned.
  • Monitor key performance metrics to drive reduction in open sorts/reworks as well as reduction in MRB inventory.
  • Maintain an audit program to assure standardized work and processes are followed.
  • Support the ongoing optimization of the processes with respect to both cost, efficiency and timeliness.
  • Develop and lead training programs and hire plans for QC team members
  • Drive timely analysis and disposition of components and products
  • Lead issue resolution in conjunction with the Quality Engineering groups for all shops in the Tesla Factory incl. root cause investigation & corrective action tracking


  • 5+ years’ experience in a technology manufacturing environment.
  • Experience working in a complex, dynamic, and fast-paced environment.
  • Detail oriented with strong record-keeping and organizational skills.
  • Proficient knowledge in applying business system applications to manage, synthesize, and interpret data.
  • Ability to operate relevant personal computing hardware and standard software
  • A deep knowledge of Lean Manufacturing practices, 5S, TPS, etc desired