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Sr. Data Engineer, Energy Service Engineering 

Tesla

Sr. Data Engineer, Energy Service Engineering 

Tesla

Palo Alto, California

·

On-site

·

Full-time

·

Today

What To Expect
We are seeking a skilled and collaborative Data Engineer to join our team. In this role, you will lead the development of data pipelines, data warehousing, and reporting infrastructure to support the growth of our energy business including Industrial, Residential, Supercharger, and Solar products. 

As a key member of our team, you will design, build, and maintain large-scale data systems to combine data from various data sources, including deployed fleets, internal applications, and other data warehouses. Your work will contribute to our understanding of key business performance indicators, informing data-driven decisions to optimize our strategies and drive decision making for all our hardware products.

You will be responsible for leading the development of data efforts that will feed into the work of downstream data analytics that will address the bookkeeping of our product genesis, usage, service and replacement cycles across our growing fleet of energy products. You will work closely with cross-functional teams, including Industrial Energy, Residential Energy, and Solar Product and Service Engineering to maximize product health of our fleet.  

What You'll Do

  • Design, develop, and maintain scalable, high-performance data pipelines and platforms supporting analytics and investigation use cases
  • Build and optimize ETL/ELT processes using Python, SQL, Apache Spark, and distributed data processing systems
  • Read, refactor, and enhance large existing codebases, improving performance and maintainability using clean OOP design principles
  • Develop and manage complex Airflow workflows (DAGs), including scheduling, dependencies, backfills, retries, and monitoring
  • Implement and support real-time / streaming pipelines using Kafka or similar technologies
  • Ensure data quality, reliability, and performance through validation, monitoring, efficient modeling, partitioning, and indexing
  • Contribute to platform architecture decisions, code reviews, best practices, and mentoring of junior engineers


  • What You'll Bring

  • Degree in Computer Science, Engineering, Mathematics, or equivalent experience
  • 2+ years of hands-on experience in data engineering, backend engineering, or similar roles where building and maintaining data systems is a primary responsibility
  • Expert-level Python proficiency, including OOP design, clean architecture, debugging, and maintaining large-scale production codebases
  • Proven ability to build scalable ETL/ELT pipelines and data models using SQL and modern data warehouses/lakes using workflow orchestration tools such as Apache Airflow (DAG design, scheduling, dependencies, monitoring)
  • Strong experience with distributed data processing frameworks such as Apache Spark (PySpark/Scala), real-time / streaming data architectures using Kafka, Spark, or similar event-driven platforms
  • Strong knowledge of software engineering fundamentals: version control (Git), testing strategies (unit/integration), code reviews, performance optimization, cloud-native and containerized environments (Docker, Kubernetes)
  • Excellent communication and collaboration skills, with the ability to work effectively across technical teams and business stakeholders


  • 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