We're seeking a highly skilled and collaborative Senior distributed systems engineer to architect and implement a cutting-edge data platform while leading the development of data pipelines, data lake, and reporting infrastructure to support the growth of our energy data platform including Industrial, Residential, Supercharger, and Solar products. You'll design large-scale data systems that integrate multiple sources including deployed fleets, internal applications, and data warehouses while developing robust monitoring and alerting infrastructure.
Your role involves building efficient batch and streaming applications that power business intelligence and support ML engineers with feature engineering infrastructure. You'll create analytics capabilities to track energy products throughout their lifecycle, from creation to deployment, usage, maintenance, and replacement.
Working cross-functionally with teams across our energy divisions, you'll leverage your expertise in data engineering to build scalable solutions that enable rapid development and deployment of data products and drive informed decision-making.
Design, develop, and operate distributed data systems that process terabyte- to petabyte-scale batch and streaming workloads across Tesla's global energy fleet
Build and optimize high-throughput pipelines on Apache Spark (PySpark, Spark SQL, Spark Streaming) and Kafka, with strong correctness and recovery guarantees - Architect the data lake on modern open table formats (Delta Lake, Apache Iceberg, or Apache Hudi) and design the partitioning, compaction, and schema-evolution strategies that make it performant at scale
Develop aggregate, summary, and feature tables that serve engineering teams across multiple product lines and geographies
Characterize complex problems around scalability, reliability, performance, and cost in production data systems, and drive them to resolution - Implement and maintain CI/CD, monitoring, and alerting for data applications, treating pipelines as production services -
Provide technical leadership, foster collaboration with ML engineers, analytics teams, and product engineering, and drive initiatives end-to-end
Build self-service tooling that lets cross-functional teams discover, consume, and understand data faster
Research and incorporate emerging data infrastructure, tools, and technologies into the platform
Strong data engineering background with expertise in at least two programming languages (Python, Scala, Java, or Rust)
Several years of industry experience designing, building, and operating large-scale distributed systems in production
3+ years of professional experience in data engineering, analytics engineering, or backend software development
Expert-level experience with Apache Spark (PySpark, Spark SQL, Spark Streaming) at terabyte-scale or larger
Hands-on experience with modern data lake technologies (Delta Lake, Apache Iceberg, or Apache Hudi)
Excellent understanding of database internals, query optimization, and SQL performance tuning
Experience with containerization and orchestration (Docker, Kubernetes) and Strong CS fundamentals including data structures, algorithms, and distributed systems
Benefits
Along with competitive pay, as a full-time Tesla employee, you are eligible for the following benefits at day 1 of hire:
Expected Compensation
$124,000 - $258,000/annual salary + cash and stock awards + benefits
Pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. The total compensation package for this position may also include other elements dependent on the position offered. Details of participation in these benefit plans will be provided if an employee receives an offer of employment.