What to ExpectThe Energy Quality Team in Nevada is looking for a Data Engineer to support Quality Engineering initiatives on site. this position will support automation of production controls, defect prediction, advanced statistics, automate data pipelines and maintaining respective databases, creating live visualization tools to enable quality assurance for Tesla Energy products.What You’ll Do Define requirements and perform validation of manufacturing execution systems Analyze manufacturing, equipment and product field data and extract useful statistics and insights about failures to drive meaningful improvements to production quality and customer experience Work effectively with Engineers and conduct end-to-end analyses, from data requirement gathering, to data processing and modeling Monitor key product metrics, understanding root causes of changes Interpret data, analyze results using statistical techniques and provide ongoing reports Identify, analyze, and interpret trends or patterns in complex data sets and depict the story via dashboards and reports Maintain existing data visualizations, data pipelines and dashboard enhancement requests Acquire data from primary or secondary data sources and maintain databases/data systems to empower operational and exploratory analysis Perform data quality validations to ensure data creation is as per the business needs and expectationsWhat You’ll Bring Bachelor’s Degree in Management Information Systems, Computer Science, Math, Physics, Engineering, Statistics or another technical field, or equivalent experience Extensive experience writing software with Python Experience with multiple data architecture paradigms (e.g. SQL, NoSQL, Kafka, Spark) Experience and interest in frontend development, preferably with the JavaScript React framework Knowledge of various data communication protocols (e.g. REST API, WebSocket) Able to work under pressure while collaborating and managing competing demands with tight deadlines Experience with open-source machine learning libraries and frameworks (Tensorflow, Keras, etc.) Familiarity with continuous integration pipelines (Docker, Jenkins, Kubernetes) Ability to drive introduction of predictive model to a production environment Success building and tuning image classification model

Sparks, Nevada

Full time