Full-Stack Software Engineer

2 weeks ago


Toa Payoh, Singapore Tesla Full time

What to Expect
- Full-stack Software Engineer

Tesla Electronics Test and Automation Group (ETAG) is the main point of contact to ensure the highest quality vehicle, silicon and robotics electronics for our customers. Our mission is to develop test automation equipment, architect software automation framework, and provide hardware/software/data infrastructure for Tesla electronics communities worldwide.

We are seeking a highly motivated and experienced Full-Stack Engineer with experience in DevOps and Data Engineering to join our Low Voltage Software team. As a member of our team, you will be responsible for developing software frameworks for internal customers to communicate with and validate microcontrollers and other embedded systems.

What You’ll Do
- Create, maintain, and expand design of internal engineering tools related to harnesses, devices, vehicles, and factory diagnostics.
- Participate in next-generation feature and tool development, system architecture definition, end-to-end implementation from early prototype to full release.
- Own and support existing tools by scaling them for use across the entire engineering organization while maintaining reliability.
- Collaborate with engineers to formulate user stories and develop designs and specifications.
- Confer and collaborate with cross-functional teams, hardware, and software teams.
- Support bring-up, validation, and development of new hardware and systems.
- Manage the infrastructure as code (IAC), allowing for better infrastructure management.
- Monitor and troubleshoot production systems using tools like Prometheus.
- Build and maintain continuous integration and delivery pipelines using tools like Jenkins CI/CD.

What You’ll Bring
- Strong programming skills with proficiency in Python and pydata stack (numpy, scipy, pandas, flask).
- Experience with containerization and orchestration tools like Docker and Kubernetes.
- Experience in designing and implementing data pipelines using tools like Apache Kafka, Apache Spark, or Apache Airflow.
- Familiarity with data modeling and database design concepts.
- Experience with SQL and NoSQL databases.
- Knowledge of data warehousing and ETL processes.
- Demonstrate engineering skills with quantitative projects.



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