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Senior Engineer, New Product Introduction - Vehicle Manufacturing (m/f/d) - Gigafactory Berlin-Brandenburg

Tesla

Senior Engineer, New Product Introduction - Vehicle Manufacturing (m/f/d) - Gigafactory Berlin-Brandenburg

Tesla

Grünheide (mark), Brandenburg

·

On-site

·

Full-time

·

Today

What To Expect
The Senior Engineer, New Product Introduction (NPI), within the Vehicle team, is responsible for the seamless integration of Vehicle changes into the production environment. This role involves cross-functional strategic coordination with Engineering, Supply Chain, and Berlin Operations teams to ensure operational readiness for each major change. Strong planning and communication skills are essential, as the role includes frequent status reporting and presentations to management.

What You'll Do

  • Lead all activities related to the implementation of coordinated Vehicle changes in the factory, ensuring alignment with company-defined milestones and seamless change integration.
  • Represent NPI in cross-functional program and manufacturing readiness forums. Provide clear, organization-wide updates and proactively identify and escalate risks.
  • Plan, coordinate, and execute all pre-launch builds and production trials to validate Vehicle changes. Ensure supply chain readiness, manage the transition from launch planning through factory implementation and ramp-up, and oversee excess/obsolescence and post-program/service activities.
  • Manage large scope projects within the Vehicle team, and Vehicle projects that overlap with other areas, such as associated Drive Unit and Vehicle launches. Lead end-to-end execution, working closely with local factory stakeholders to align plans, deliver updates, and highlight risks.
  • Finalize and validate the Manufacturing Bill of Materials (MBOM), and ensure all supporting factory systems (MRP, ERP, MES, etc.) are ready for launch.
  • Define and manage the overall validation and manufacturing readiness plan, including key performance indicator (KPI) tracking.
  • Ensure environmental, health, and safety (EHS) considerations are integrated into all validation and production activities.
  • Track and resolve open issues to support a smooth launch and ensure timely communication through regular status reports and issue-resolution summaries.
  • Collaborate and drive alignment with local cross-functional teams, including Engineering, Manufacturing, Supply Chain, Quality, Production, Production Control, Sales, and Service.
  • Support additional tasks as needed to assist NPI or broader production teams.
  • Participate in regular knowledge-sharing sessions with NPI peers across Battery, Drive Unit, and Vehicle teams.
  • Full competency in core NPI tools, namely: Warp BOM, FX, Warp MRP, POs, JIRA, Confluence, PCA, Production Garage & Dplan.


  • What You'll Bring

  • Minimum 5 years’ experience in similar roles and environment.
  • Bachelor’s degree in engineering or related technical field required (Master’s Degree in supporting field highly preferred).
  • Production Operations Knowledge - Has a firm understanding of how complex production lines operate including key items such as industrial workings between facilities/departments, line balance, OEE, error proofing, etc.
  • Background in manufacturing/industrial engineering required, supply chain highly desired.
  • Understanding of how the manufacturing validation process runs in relation to complex new products that stretch across various engineer teams and manufacturing centers/factories (methodology, validation plans, associated KPIs).
  • Great understanding of design for manufacture, process design, process validation, and assembly methods.
  • Strong interpersonal skills dealing with all levels of an organization. Able to communicate to senior and executive level leadership effectively and confidently.
  • Strong written and verbal communication skills. Well versed with common workplace software (word processor, spreadsheet, database, etc). Excellent organizational skills
  • Able to be a creative thinker and devise creative solutions to complicated problems
  • Excellent problem-solving skills; adverse in various problem solving methodologies
  • Team player; ability to work in a fast-paced, multi-cultural environment with cross-functional teams
  • Previous experience with Manufacturing Execution Systems (MES)
  • Previous experience with ERP systems (SAP, Oracle, etc)
  • Ability to read and interpret basic mechanical drawings or CAD models
  • Has a well-versed understanding of production line layout, flow, and modeling.
  • Should clearly understand the following:
  • job shops, batch and flow production
  • takt, touch and cycle time
  • bottle neck identification and methods for resolving
  • work station organization and setup / lean manufacturing principles
  • statistical process control
  • designing single flow lines to build multiple products
  • Minimum eight years’ experience in automotive, high tech, or other high volume/high complexity manufacturing in a similar capacity coupled with demonstration of exceptionable ability.
  • Strong motivation to support the company mission is necessary to succeed


  • , Tesla

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    About Tesla

    Tesla

    Tesla

    Public

    A financial leasing taxi company that provides vehicles to customers

    140,000+

    Employees

    Ciudad De Panamá

    Headquarters

    $800B

    Valuation

    Reviews

    3.1

    5 reviews

    Work Life Balance

    1.5

    Compensation

    1.2

    Culture

    1.3

    Career

    1.8

    Management

    1.1

    15%

    Recommend to a Friend

    Pros

    Strong financial performance

    Revenue growth

    Company achieving targets

    Cons

    Poor compensation and raises below inflation

    Union-busting and anti-labor practices

    Unpaid work demands and wage theft

    Salary Ranges

    3,570 data points

    Junior/L3

    Mid/L4

    Junior/L3 · Associate Analyst

    2 reports

    $94,875

    total / year

    Base

    $82,500

    Stock

    -

    Bonus

    -

    $92,000

    $97,750

    Interview Experience

    4 interviews

    Difficulty

    3.5

    / 5

    Duration

    14-28 weeks

    Experience

    Positive 0%

    Neutral 75%

    Negative 25%

    Interview Process

    1

    Application Review

    2

    Recruiter Screen

    3

    Technical Phone Screen

    4

    Take-home Assignment

    5

    Panel Interview

    6

    Offer

    Common Questions

    Coding/Algorithm

    Technical Knowledge

    Behavioral/STAR

    System Design

    Machine Learning Concepts