招聘
What to Expect
The Engineering Technician is responsible for supporting in Developing, implementing, and optimizing remanufacturing processes for Tesla parts and systems (including batteries, drivetrains, and power conversion units) around the world.
Interact with engineers from our design, manufacturing, test, and quality teams, as well as our production staff to improve field failure diagnostics and remanufacturing efficiency. Monitor equipment trends and carry out trial experiments for new products and processes. Utilize experimental data, models and statistical methods to quickly support engineers with analysing complicated problems and large data sets. Support with the implementation of KPIs to track progress in key areas, such as safety, throughput, quality, and labour efficiency.
The goal is to minimize refurbishment, manufacturing, and warranty costs, by optimizing quality, failure analysis, and manufacturing processes.
What You'll Do
- Failure Analysis & Root Cause Investigation: Conduct detailed failure analysis on returned parts (cells, PCBAs, SW/FW) to identify root causes and drive corrective actions
- Data-Driven Insights: Analyze vehicle logs, service databases, repair orders, and production data to inform quality improvements and process optimizations
- Process Development & Documentation: Collaborate globally to design, document, and refine remanufacturing workflows (flowcharts, work instructions) and maintain accurate records
- KPI Monitoring & Continuous Improvement: Track and improve KPIs for production efficiency, quality, safety, and cost; support trials for process validation and safety initiatives
- New Part Introduction Support: Facilitate NPI activities, including action item follow-up and manufacturing trials to ensure functionality, quality, and safety compliance
- Workplace Safety & Organization: Maintain 5S practices, ensure orderly workspaces, and uphold safety protocols while addressing production-critical discrepancies
What You'll Bring
- Education/Experience: High school diploma (technical field) or equivalent. 1+ years in manufacturing problem-solving, with experience in data analysis (Python/SQL preferred) and electro-mechanical assembly (e.g., motors, batteries)
- Technical Skills: Ability to interpret electrical diagrams/mechanical drawings, use hand tools, and familiarity with semi-automated manufacturing systems. Automotive powertrain/EV component experience (e.g., batteries, AC/DC systems) is a plus
- Physical Requirements: Capable of lifting 23 kg, using precision tools, and performing hands-on assembly/testing
- Analytical Focus: Experience analyzing large datasets, troubleshooting production issues, and optimizing processes through data-driven insights
- Soft Skills: Strong communication, teamwork, adaptability, and ability to manage multiple tasks in a fast-paced, cross-functional environment
- Industry Fit: Ideal for candidates with automotive/EV manufacturing backgrounds, emphasizing quality control, diagnostics, and process improvement
- Eligibility to work in the Netherlands (EU citizenship or valid work permit) is required
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About Tesla

Tesla
PublicA 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
News & Buzz
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Source: The Guardian
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