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Tesla Looking For Software Engineer, Data Engineering, Toolbox Software at Palo Alto, CA Full Time
The Role
Data is deeply embedded in the product and engineering culture at Tesla. We collect data from our vehicle fleet and use it to support service and engineering in identifying issues at the fleet or vehicle level, enabling diagnostic automation and technician workflow to identify issues and take corrective actions. We’re looking for a talented engineer to join us in analyzing and reporting on data, creating ETL processes, and implementing improvements to our data platform. Your work will affect thousands of technicians and Tesla engineers daily, enabling them to keep our vehicle fleet on the road and improve customer experience.
Data is deeply embedded in the product and engineering culture at Tesla. We collect data from our vehicle fleet and use it to support service and engineering in identifying issues at the fleet or vehicle level, enabling diagnostic automation and technician workflow to identify issues and take corrective actions. We’re looking for a talented engineer to join us in analyzing and reporting on data, creating ETL processes, and implementing improvements to our data platform. Your work will affect thousands of technicians and Tesla engineers daily, enabling them to keep our vehicle fleet on the road and improve customer experience.
Responsibilities
Develop analysis and reporting focused on operational, technical metrics and KPIs
Deliver quick turnarounds on dashboards, identify trends and/or issues within data sets, and make recommendations to influence business decisions and investments
Improve our data platform by improving performance, stability and maintainability of our relational databases, ETL pipelines, queue (Kafka, RabbitMQ) environments
Evaluate the effectiveness of engineering initiatives and deliver actionable insights to improve service productivity
Present analytical results and insights to business partners to answer strategic questions and influence business decisions
Requirements
Minimum of 2-3 years of experience in a data analytics related capacity
Understanding of relational database theory and proficiency in writing, understanding, and optimizing complex SQL code
Software engineering fundamentals
Experience with Business Intelligence tools (eg Tableau or Superset) and real time dashboard development
Experience with Jupyter, Pandas workflow
Understanding of queue-based environments including Kafka or AMQP
Robust DevOps abilities and a strong predilection for automation
Strong communication, organizational, and analytical and problem solving skills
Strong business acumen
Nice to Have
Knowledge of statistical models, predictive model development (Python, R, SAS, etc), machine learning, proficiency in Spark
