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Tesla

Accelerating the world's transition to sustainable energy.

Equipment Engineer Drive Unit (m/w/d) - Gigafactory Berlin-Brandenburg

职能工程
级别中级
地点Grünheide (mark), Brandenburg, Germany
方式现场办公
类型全职
发布今天
立即申请
What To Expect
The Equipment Engineer in the Equipment Engineering team will be a part of operating, sustaining, and improving some of the most automated manufacturing equipment in the world. The best candidate for the position has a high aptitude to learn new skillsets in the position. This role requires capability across the board to sustain all parts of the automated equipment. The expectation is not that you arrive on day 1 with this capability, but that you have the attitude and desire to learn all aspects of automation.

What You'll Do

  • Work collaboratively with design, product excellence, production operations, Manufacturing Engineering, NPI, Process Engineering, Maintenance and other cross functional teams as the expert to ensure production lines run in a safe, efficient manner producing high quality parts.
  • Continuous monitoring of compliance with safety standards and regulations relating to production equipment.
  • Prioritize and lead equipment improvement projects to increase Machine availability and Cost reduction for assigned equipment
  • Support line maintenance and process engineers in troubleshooting and repair of equipment
  • Develop and implement strategies for preventive and predictive maintenance.
  • Set up, maintain, and improve the CMMS system.
  • Build training material, maintenance routines, and related documentation for equipment life cycle management.
  • Challenge Product Specifications and Packaging Specifications
  • Creating and maintaining technical documentation, including specifications and operating instructions.
  • Lead equipment upgrades with focus on serviceability and equipment reliability.
  • serviceability and reliability for assigned equipments
  • Training of technical staff for assigned equipment and technologies.
  • Identify equipment critical spare parts and ensure sufficient coverage to prevent extended downtime situations.
  • 3D CAD and design of equipment.


  • What You'll Bring

  • Bachelor's degree in Mechanical Engineering or Electrical Engineering or equivalent
  • Minimum 3 years of experience in maintenance and repair of production equipment
  • Experience in interpreting technical documents and manuals
  • Experience in creating and maintaining operating and training documents
  • Knowledge of pneumatics, hydraulics, cooling systems, and vacuum technology
  • Experience with electronic devices and systems
  • Strong communication skills with various stakeholders, English is a plus
  • Strong analytical and problem solving skills (DMAIC, 8D, ISHIKAWA, 5W.).
  • Able to work under intense time pressure in the presence others.
  • Willing to work days, afternoons and weekends as determined by project needs.


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    关于Tesla

    Tesla

    Tesla

    Public

    A financial leasing taxi company that provides vehicles to customers

    140,000+

    员工数

    Ciudad De Panamá

    总部位置

    $800B

    企业估值

    评价

    10条评价

    3.8

    10条评价

    工作生活平衡

    2.3

    薪酬

    4.0

    企业文化

    3.2

    职业发展

    4.1

    管理层

    2.8

    65%

    推荐率

    优点

    Innovative projects and cutting-edge technology

    Great team and supportive colleagues

    Good compensation and benefits

    缺点

    Long hours and poor work-life balance

    High pressure and tight deadlines

    Management issues and high expectations

    薪资范围

    1,403个数据点

    Junior/L3

    Mid/L4

    Junior/L3 · Associate Analyst

    2份报告

    $94,875

    年薪总额

    基本工资

    $82,500

    股票

    -

    奖金

    -

    $92,000

    $97,750

    面试评价

    4条评价

    难度

    3.5

    / 5

    时长

    14-28周

    体验

    正面 0%

    中性 75%

    负面 25%

    面试流程

    1

    Application Review

    2

    Recruiter Screen

    3

    Technical Phone Screen

    4

    Take-home Assignment

    5

    Panel Interview

    6

    Offer

    常见问题

    Coding/Algorithm

    Technical Knowledge

    Behavioral/STAR

    System Design

    Machine Learning Concepts