What To Expect
The manufacturing quality data engineering team is a high impact, high priority and high visibility team that is laser focus on safety critical issues and expanding critical services to Gigafactories worldwide. Within Tesla's Vehicle Engineering organization, you will have the data gold mines across design, manufacturing and vehicle data sources, enabling you to design, create and deploy innovative new data services, automation and machine learning tools into production use. In this role, you will focus on scaling the exponentially growing infrastructure reliably, leveraging testing automation infrastructure to detect software issues before customers experience them.
What You'll Do
Led the design, implementation, and optimization of automated testing frameworks for large-scale web and mobile applications, utilizing tools such as Selenium, Appium, and Cypress to achieve high test coverage and significantly improve product reliability across multiple release cyclesCollaborated with cross-functional teams, including software engineers, product managers, DevOps engineers and data engineers, to integrate automated testing into CI/CD pipelines using Jenkins, ensuring seamless deployment and minimizing production downtime through proactive failure detectionDeveloped and maintained comprehensive test automation suites in Java, Python, and JavaScript, incorporating behavior-driven development (BDD) principles with Cucumber to facilitate scalable, maintainable tests that supported agile sprints and rapid iteration on features serving millions of usersConducted in-depth code reviews and mentored junior QA engineers on best practices for test automation, including API testing with Postman, resulting in noticeable improvements in team efficiency and the establishment of standardized testing protocols across the organizationAnalyzed test results and defect patterns using data-driven approaches, leveraging tools like JIRA and TestRail for tracking, and implemented