Sr. Distributed Systems Engineer, Energy Service Engineering

Sr. Distributed Systems Engineer, Energy Service Engineering Tesla

• 3.3 Palo Alto, CA Job Details Full-time $124,000
• $258,000 a year 8 hours ago Benefits Commuter assistance Health savings account AD&D insurance Paid holidays Disability insurance Health insurance Dental insurance Flexible spending account Flextime Adoption assistance Employee assistance program 401(k) matching Employee discount Benefits from day one Pet insurance Qualifications Containerization systems Software engineering Data structures Research Scalable systems Algorithms Scalability Distributed computing System tuning Query management Full Job Description What to Expect 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. What You'll Do 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 What You'll Bring 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 Compensation and Benefits Benefits Along with competitive pay, as a full-time Tesla employee, you are eligible for the following benefits at day 1 of hire: Medical plans > plan options with $0 payroll deduction Family-building, fertility, adoption and surrogacy benefits Dental (including orthodontic coverage) and vision plans, both have options with a $0 paycheck contribution Company Paid (Health Savings Accounts) HSA Contribution when enrolled in the High-Deductible medical plan with HSA Healthcare and Dependent Care Flexible Spending Accounts (FSA) 401(k) with employer match, Employee Stock Purchase Plans, and other financial benefits Company paid Basic Life, AD&D Short-term and long-term disability insurance (90 day waiting period) Employee Assistance Program Sick and Vacation time (Flex time for salary positions, Accrued hours for Hourly positions), and Paid Holidays Back-up childcare and parenting support resources Voluntary benefits to include: critical illness, hospital indemnity, accident insurance, theft & legal services, and pet insurance Weight Loss and Tobacco Cessation Programs Tesla Babies program Commuter benefits Employee discounts and perks program 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. Tesla is an Equal Opportunity / Affirmative Action employer committed to diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, age, national origin, disability, protected veteran status, gender identity or any other factor protected by applicable federal, state or local laws. Tesla is also committed to working with and providing reasonable accommodations to individuals with disabilities. Please let your recruiter know if you need an accommodation at any point during the interview process.