Sr. Software Engineer, Data Platform, Factory Software

What To ExpectTesla's Factory Software team builds the systems that keep our factories running — and the data layer underneath all of it is what makes real-time decisions, AI automation, and operational intelligence possible. As we scale software across every gigafactory worldwide, we need a data platform that can keep up: high-throughput ingestion, sub-second analytics, and a foundation that AI agents can actually reason over.That's where you come in. You'll own ClickHouse as a core platform — not as a DBA maintaining a box, but as an engineer building the storage backbone that powers every application, pipeline, and AI agent in our factory software ecosystem. You'll define how data flows in, how it's modeled, how it's queried at scale, and how AI agents consume it to drive autonomous decisions on the factory floor.This isn't an IT support role. It's a platform engineering role with direct impact on production output across Tesla's global manufacturing operations.What You'll DoOwn the design, deployment, and operation of ClickHouse clusters across factory software applications — schema design, table engine selection, partitioning, replication, and retention strategiesBuild and maintain high-throughput data ingestion pipelines from factory systems, IoT devices, Kafka streams, and operational databases into ClickHouseDefine data modeling standards and query patterns that enable consistent, performant access across engineering teams — establish ClickHouse as the source of truth for analytical and operational workloadsDesign and expose data access layers (APIs, SDKs, materialized views) that AI agents and LLM-based workflows can reliably query and act onCollaborate with application engineers to migrate existing workloads to ClickHouse where appropriate, and advise on storage architecture decisions across MySQL, PostgreSQL, Elasticsearch, and MongoDBInstrument and own observability for the data platform — query performance, ingestion lag, cluster health, alerting, and capacity planningDeploy and operate data platform services on Kubernetes with full CI/CD ownership and on-call accountabilityDrive adoption across the engineering org through documentation, internal tooling, design reviews, and hands-on enablement — you're the ClickHouse authority teams reach for, not the IT ticket queueStay current with the ClickHouse ecosystem as it evolves — evaluate releases and new engine capabilities so our platform tracks upstream best practicesWhat You'll BringDegree in Computer Science, Software Engineering, or a related field, or equivalent experience 5+ years of backend or data engineering experience, with 2+ years of hands-on ClickHouse in production — you've designed schemas, tuned queries, and operated clusters under real load, not just ran tutorialsDeep understanding of ClickHouse internals: MergeTree family engines, materialized views, projections, dictionaries, sharding, replication, and query optimization; index-aware table design (ORDER BY, primary key, data-skipping indexes) and tuning; production troubleshooting — diagnosing errors such as excessive parts ("too many parts"), replication lag, and related cluster issues; performance analysis under concurrency and load, not only optimizing isolated queriesStrong proficiency in SQL for analytical workloads and at least one systems/backend language — Go, Python, Rust, or C# — for building services and pipelines around the data layerExperience with streaming data ingestion — Kafka, Kinesis, or equivalent — and designing low-latency pipelines from event sources into columnar storageSolid grasp of distributed systems fundamentals: consistency trade-offs, fault tolerance, backpressure, and schema evolution under live trafficHands-on experience enabling AI/ML workloads with data infrastructure — building data layers that support RAG pipelines, LLM tool-use, agent memory, or real-time feature servingExperience deploying and operating data services on Kubernetes, with strong observability practices (metrics, tracing, alerting)Ability to work across engineering teams as a platform owner — you write design docs, do code reviews, and raise the floor on data quality for everyone, not just your own servicesThrive in a high-autonomy, fast-moving environment where you're expected to define the right solution, not just execute a ticketBenefitsCompensation and BenefitsAlong 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 programExpected Compensation$168,000 - $252,000/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., Tesla