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Data Engineer, Optimus

Tesla

Data Engineer, Optimus

Tesla

Fremont, California

·

On-site

·

Full-time

·

Today

What To Expect
Tesla is seeking a Data Engineer to join our Optimus production engineering team and play a critical role in scaling our production analytics infrastructure. In this role, you will design, build, and optimize large-scale data pipelines and systems that enable high-quality reporting, advanced analytics, and real-time insights across Tesla’s manufacturing operations. You will work with cross-functional engineering, operations, and analytics teams to ensure that data is accurate, timely, and actionable— helping drive improvements in product quality, production efficiency, and decision-making. Expect to work in a fast-paced, high-energy environment where your work directly supports Tesla’s mission to accelerate the world’s transition to sustainable abundance.

What You'll Do

  • Design, build, and maintain scalable data pipelines and ETL frameworks for manufacturing and operational data
  • Partner with engineers, analysts, and business stakeholders to translate requirements into robust data models and architecture
  • Develop and optimize SQL queries, stored procedures, and views across multiple database systems
  • Implement data quality checks, monitoring, and validation processes to ensure reliability and accuracy of KPIs and dashboards
  • Integrate diverse data sources, including IoT, MFS, FX, and WARP systems, into unified data models
  • Build automation frameworks for data ingestion, transformation, and orchestration using Airflow or similar tools
  • Collaborate with data visualization teams to enable interactive dashboards and analytics for operations and leadership
  • Ensure data security, governance, and best practices in system design and usage
  • Drive continuous improvement in data infrastructure, performance tuning, and scalability
  • Integrate factory AI resources into streamlined data analysis, enhancing efficiency and accuracy in manufacturing operations


  • What You'll Bring

  • Degree in Computer Science, Data Engineering, Information Systems, or equivalent experience
  • 4+ years of experience in data engineering, preferably supporting manufacturing, operations, or industrial analytics
  • Strong expertise in SQL and experience with multiple database platforms (MySQL, MS SQL Server, Oracle, Vertica, ClickHouse, or similar)
  • Proficiency in Python for data engineering and automation (pandas, PySpark, or similar frameworks)
  • Hands-on experience with distributed data processing technologies such as Spark, Kafka, or Flink
  • Experience with orchestration and workflow management tools (Airflow, Prefect, or Luigi)
  • Solid understanding of data warehousing concepts, dimensional modeling, and schema design
  • Familiarity with containerized & cloud-based deployment (Docker, Kubernetes, AWS, GCP or Azure)
  • Experience with BI and visualization tools such as Tableau, Power BI, or Superset and strong communication skills and ability to collaborate across engineering and business functions
  • Passion for building scalable, reliable data systems that drive measurable impact in a manufacturing environment


  • Benefits
    Compensation and 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

    $100,000 - $216,000/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.

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    About Tesla

    Tesla

    Tesla

    Public

    A financial leasing taxi company that provides vehicles to customers

    140,000+

    Employees

    Ciudad De Panamá

    Headquarters

    $800B

    Valuation

    Reviews

    3.1

    5 reviews

    Work Life Balance

    1.5

    Compensation

    1.2

    Culture

    1.3

    Career

    1.8

    Management

    1.1

    15%

    Recommend to a Friend

    Pros

    Strong financial performance

    Revenue growth

    Company achieving targets

    Cons

    Poor compensation and raises below inflation

    Union-busting and anti-labor practices

    Unpaid work demands and wage theft

    Salary Ranges

    3,570 data points

    Junior/L3

    Mid/L4

    Junior/L3 · Associate Analyst

    2 reports

    $94,875

    total / year

    Base

    $82,500

    Stock

    -

    Bonus

    -

    $92,000

    $97,750

    Interview Experience

    4 interviews

    Difficulty

    3.5

    / 5

    Duration

    14-28 weeks

    Experience

    Positive 0%

    Neutral 75%

    Negative 25%

    Interview Process

    1

    Application Review

    2

    Recruiter Screen

    3

    Technical Phone Screen

    4

    Take-home Assignment

    5

    Panel Interview

    6

    Offer

    Common Questions

    Coding/Algorithm

    Technical Knowledge

    Behavioral/STAR

    System Design

    Machine Learning Concepts