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Data Engineer, Energy Hardware Engineering

Tesla

Data Engineer, Energy Hardware Engineering

Tesla

Palo Alto, California

·

On-site

·

Full-time

·

Today

Required Skills

Python

SQL

Docker

Kubernetes

Git

Kafka

Spark

Tableau

Machine Learning

What To Expect
The Tesla Energy Products Field Quality team is looking for a passionate and collaborative Data Engineer to join the team and leverage data and analytics to ensure the best customer experience and fleet reliability across the Tesla Energy portfolio; Industrial, Residential, Supercharger, and Solar. In the Energy Products Field Quality Data Engineering role, you will identify fleet-wide part performance trends, operation, and maintenance challenges across the growing fleet of energy products. The Fleet Data Engineer’s primary role is to leverage real-world performance and maintenance data to drive fleet-wide improvements by identifying trends and determining effective strategies to improve key fleet health metrics. A significant aspect of this position involves using various technologies to accelerate engineering progress, including ML / AI. This position is well suited for curious, inventive, and adventurous Engineers who want to solve problems with data and aren’t afraid to venture into the unknown and untested when required. As part of the team, you will be enabled to work across the organization to solve problems and ensure the success of our products working alongside Industrial Energy, Residential Energy, and Solar Product & Design Engineers. Our teams operate with a non-conventional philosophy of interdisciplinary collaboration. Each member of the team is expected to challenge and to be challenged, to create, and to innovate. We’re tackling the world’s most difficult and important problems—and we wouldn’t succeed without our shared passion for making the world a better place.

What You'll Do

  • Perform statistical analysis to quantify reliability risks and identify emerging failure trends
  • Utilize large scale fleet telemetry data for diagnostics and prognostics
  • Maintain and scale data pipelines/ tables & applications within the Field Quality team
  • Create coherent and consistent dashboards / data visualization applications
  • Build Field quality data tooling around internal chat based agentic applications


  • What You'll Bring

  • Strong Python, especially in a data analytics/science capacity where pandas/numpy are used heavily (matplotlib/seaborn/plotly/etc.)
  • Experience with multiple data architecture paradigms (SQL, NoSQL, Kafka, Spark)
  • Knowledge of various data communication protocols (REST API, Websockets)
  • Experience with version control (Git)
  • Familiarity with continuous integration pipelines (Docker, Jenkins, Kubernetes)
  • Strong analytical skills and knowledge of applied statistics including predictive analytics, time series analysis and machine learning
  • Knowledge of tooling around LLMs (MCP, A2A etc.) and ML applied to timeseries
  • Tableau (or, similar BI tools), Any opensource/freeware viz tools (e.g., D3, ggplot)
  • Ability to quickly learn new technologies
  • Degree in Computer Science, Physics, Electrical Engineering, or equivalent experience


  • 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