Data Engineer - Paintshop at Tesla Gigafactory Berlin-Brandenburg

About the Role

Tesla is driving transformative innovation within the automotive sector by leveraging sustainable energy and cutting-edge manufacturing techniques. As a Data Engineer situated in the Paint Shop at the Gigafactory Berlin-Brandenburg, you will utilize production data to enhance paint processes, assist in quality control, and boost operational efficiency. Collaborating closely with senior engineers, your role involves developing and sustaining data pipelines that pull in real-time information from paint lines, inspection devices, and automation systems. These efforts facilitate the generation of comprehensive datasets and dashboards crucial to the team’s success.

Working hand in hand with cross-disciplinary teams — including Production Engineering, Controls, and Quality departments — you will empower data-driven strategies that accelerate Tesla's mission of delivering high-volume, flawless vehicle production rooted in sustainable energy principles. This position is crafted for an engineer possessing a strong technical background seeking substantive impact in a swift, manufacturing-centric environment.

Key Responsibilities

• Create, maintain, and refine ETL pipelines capturing data from Paint Shop infrastructure like sensor arrays on coating robots, inspection cameras, and cycle time tracking equipment.
• Design and integrate diverse manufacturing data sources, such as automated assembly lines, environmental health and safety sensors, and ERP platforms, consolidating them into unified datasets for detailed analysis.
• Manage and optimize data storage solutions including lakes, warehouses, and real-time streams to support monitoring vital paint quality parameters, defect statistics, and throughput rates.
• Deliver dynamic dashboards and rigorous data validation efforts to guarantee precise, complete, and trustworthy data outputs that meet production and defect tracking needs.
• Continuously assess and enhance existing data workflows aimed at minimizing latency while maximizing accuracy, adhering to data governance and compliance frameworks, especially relating to EHS standards.
• Collaborate with Paint Shop personnel—supervisors, engineers, analysts—to accurately translate operational data requisites into technical solutions, including automated reporting mechanisms.
• Engage in problem-solving initiatives utilizing advanced technologies such as machine learning for anomaly detection in paint defects and IoT data integration; contribute to sustaining and expanding the Internal Surface Vision System (iSVS) for defect classification.
• Identify and recommend process improvements, including strategies to reduce paint material waste driven by insightful data analytics, while broadening expertise across the technology stack.
• Document all data pipelines and procedures you manage, ensuring compliance with Tesla's stringent safety protocols, data privacy laws such as GDPR, and sustainability objectives.

Applicant Qualifications

• Possess a Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a closely related discipline, or demonstrate equivalent hands-on experience.
• Have at least two years’ professional experience in data engineering or similar roles, preferably with exposure to manufacturing, automotive, or industrial datasets.
• Show proficiency in Python programming (knowledge of Java or Scala is advantageous).
• Demonstrate hands-on experience or willingness to work with data pipeline architectures and big data/streaming platforms like Apache Spark or Kafka.
• Exhibit strong SQL competencies (e.g., PostgreSQL, MySQL); familiarity with NoSQL databases and orchestration platforms like Airflow is considered a bonus.
• Understand API integrations and version control systems, notably Git.
• Possess strong analytical problem-solving skills and are able to communicate effectively across technical and non-technical stakeholders in dynamic, high-pressure settings.
• Be prepared to work within a manufacturing environment, with flexible shift schedules as needed, and successfully complete Tesla’s background verification and safety training processes.

Preferred Skills and Interests

• Experience working with Manufacturing Execution Systems (MES), IoT frameworks, or data visualization software such as Tableau or Power BI.
• Basic knowledge regarding manufacturing workflows, including paint application procedures, quality assurance inspections, and environmental health and safety compliance.
• Interest in integrating machine learning or artificial intelligence into predictive analytics for manufacturing environments, notably with systems like iSVS.