Sr. Distributed Systems Engineer, Energy Service Engineering in , United States

Senior Distributed Systems EngineerWe'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 streaming data pipelines, data lake, and OLAP 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.ResponsibilitiesDesign, develop, and operate distributed data systems that process streaming and batch workloads at terabyte- to petabyte-scale across Tesla's global energy fleet, against sub-minute end-to-end latency SLAsBuild streaming pipelines on Apache Spark Structured Streaming and Kafka with exactly once correctness and recovery guarantees, and evaluate complementary stream-processing engines (Apache Flink, Kafka Streams, Akka Streams, or Apache Beam) where it's the right frameworkArchitect high-throughput ingest paths from Kafka into the Lakehouse and into low-latency OLAP stores (ClickHouse, Druid, Pinot), including schema and codec design (Protobuf, Avro, Flatbuffers) and backpressure handlingArchitect the Lakehouse on Delta Lake / Apache Iceberg / Apache Hudi with streaming-aware partitioning, compaction, CDC/upsert, and schema-evolution strategies; develop aggregate, summary, and real-time feature tables for engineering, analytics, and ML teams across product lines and geographiesDrive complex problems around scalability, reliability, performance, and cost to resolution including stateful-streaming concerns like watermarks, late-arriving data, state backends, and checkpoint/savepoint recoveryOwn CI/CD, monitoring, alerting, SLOs, and on-call for data applications treating pipelines as production services and provide technical leadership in close partnership with ML engineers, analytics, and product engineeringBuild self-service tooling that lets cross-functional teams discover and consume streaming and batch data faster, and research and incorporate emerging stream-processing and data infrastructure into the platformRequirementsStrong data engineering background with expertise in at least two programming (Python, Scala, Java, or Rust)Several years of industry experience designing, building, and operating large-scale distributed data systems in production, with at least 3+ years focused on data engineering or analytics engineeringProduction experience with at least one stream-processing engine (Apache Spark Structured Streaming, Apache Flink, Kafka Streams, Akka Streams, or Apache Beam) operating at terabyte-scale throughput or sub-minute latencyDeep working knowledge of Apache Kafka (or equivalent log/broker such as Pulsar or Kinesis) as a production backbone: partitioning, consumer-group semantics, delivery guarantees, schema management, and backpressure handlingOptimizing end-to-end streaming latency from source to sink while balancing throughput, cost, and correctness guaranteesSolid grasp of streaming fundamentals: event-time vs. processing-time, watermarks, exactly once semantics, stateful operators, and checkpoint/recoveryHands-on experience with modern data lake technologies (Delta Lake, Apache Iceberg, or Apache Hudi) and containerization/orchestration (Docker, Kubernetes)Compensation & BenefitsBenefitsAlong 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 deductionFamily-building, fertility, adoption and surrogacy benefitsDental (including orthodontic coverage) and vision plans, both have options with a $0 paycheck contributionCompany Paid (Health Savings Accounts) HSA Contribution when enrolled in the High-Deductible medical plan with HSAHealthcare and Dependent Care Flexible Spending Accounts (FSA)401(k) with employer match, Employee Stock Purchase Plans, and other financial benefitsCompany paid Basic Life, AD&DShort-term and long-term insurance (90 day waiting period)Employee Assistance ProgramSick and Vacation time (Flex time for salary positions, Accrued hours for Hourly positions), and Paid HolidaysBack-up childcare and parenting support resourcesVoluntary benefits to include: critical illness, hospital indemnity, accident insurance, theft & legal services, and pet insuranceWeight Loss and Tobacco Cessation ProgramsTesla Babies programCommuter benefitsEmployee discounts and perks programExpected Compensation $124,000 - $258,000/annual salary + cash and stock awards + benefitsPay 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.