Staff Data Engineer, Energy Service Engineering

What To Expect

Tesla is seeking a highly skilled and collaborative Staff Data Engineer (Big Data) to join our team and drive the development of data pipelines and analytics tooling to support the growth of our energy business, including Industrial, Residential, Supercharger, and Solar products. 
As a key member of our team, you will design, build, and maintain large-scale data systems to extract insights from various data sources, including deployed fleets, internal applications, and other data warehouses. Your work will contribute to our understanding of key business performance indicators, informing data-driven decisions to optimize our strategies and drive business growth.  You will be responsible for leading the development of data efforts to identify and resolve fleet-wide performance, operation, and maintenance challenges across our growing fleet of energy products. You will work closely with cross-functional teams, including Industrial Energy, Residential Energy, and Solar Product and Service Engineering, to maximize product health of our fleet. 
If you're passionate about driving the development of scalable data systems and pipelines, we’d love to hear from you! 

What You’Ll Do

• Derive an overall strategy of data management, within an established information architecture that allows us to scale data processing effectively
• Gather and process raw, structured, semi-structured, and unstructured data using batch and real-time data processing frameworks 
• Optimize existing pipelines for improved reliability, efficiency, and scalability 
• Develop aggregate and summary tables for various engineering teams that span across multiple product lines and geographies 
• Design and develop new systems and tools to enable cross functional teams to consume and understand data faster 
• Research and incorporate emerging software infrastructures, tools, and technologies, especially pertaining to big data processing
• Mentor and lead data engineers providing technical guidance and oversight 

What You’Ll Bring

• Degree in Computer Science, Engineering, Physics, or related quantitative field  or equivalent professional experience
• Experience experience in building, deploying, and maintaining Spark-based data pipelines;  additional experience with Presto/Kafka/Flink and other distributed computing engines a plus
• Experience with distributed storage such as Iceberg/Hudi/Delta parquet-based formats
• Experience with SQL and familiarity with database internals and performance concepts
• Knowledge of various data communication protocols (e.g., REST API, GRPC) 
• Proficiency in Python/Other programming languages like Scala or Java 

Additional, Preferred Experience:

• Airflow or Workflow orchestration tools like DAGster, Luigi etc. 
• Familiarity with containerization and infrastructure-as-code (Docker, Kubernetes, Terraform) 
• Strong experience with cloud data platforms (AWS, GCP, or Azure) 
• Experience with Dev-ops capabilities and familiarity with Linux 
• Experience with power generation/storage devices
• Strong dev-ops capabilities and bias for automation