Sr. Data Engineer, Energy, Sales, & Services

What Tesla offers

• Medical plans with multiple options and no employee contribution required
• Benefits for family-building, fertility, adoption, and surrogacy
• Dental (including orthodontics) and vision plans with options that require no payroll deduction
• Employer Health Savings Account contributions when enrolled in a high deductible plan with HSA
• Healthcare and Dependent Care FSAs
• 401(k) with company match and Employee Stock Purchase Plan plus other financial benefits
• Company-paid Basic Life and AD&D coverage
• Short-term and long-term disability insurance with a 90 day waiting period
• Employee Assistance Program
• Sick and vacation time, with flex time for salaried roles and accrued hours for hourly roles, plus paid holidays
• Back-up childcare and parenting support resources
• Voluntary benefits including critical illness, hospital indemnity, accident insurance, theft and legal services, and pet insurance
• Weight loss and tobacco cessation programs
• Tesla Babies program
• Commuter benefits
• Employee discounts and perks program

Compensation

Salary range of $120,000 to $216,000 per year, plus cash and stock awards and benefits. The final offer may vary based on location, experience, and qualifications, and the overall package may include other elements. Details are provided with an employment offer.

What to expect in this role

We are seeking a technically exceptional, business‑driven data engineer who operates at the crossroads of data innovation and clean energy impact. If using data to advance renewable energy, especially solar and energy storage, motivates you, this is the role to help build the intelligent infrastructure that powers a sustainable future.

As a Senior Data Engineer, you will connect state‑of‑the‑art data infrastructure with solar and storage initiatives. You will turn data into a strategic asset that optimizes generation, storage, distribution, and grid reliability, driving sustainability outcomes.

You will design and implement scalable data pipelines to process both real‑time and historical data, manage complex datasets, and collaborate with business stakeholders, energy analysts, and operations teams. Your work will enable automation, innovation, and data‑driven decisions across the energy business.

Responsibilities

• Design and deploy automated data solutions for teams across sales, operations, fulfillment, inventory, fleet, service, finance, and accounting
• Own ideas from design through production, partnering with stakeholders and cross‑functional teams
• Develop, manage, and optimize high‑performance ETL pipelines that turn complex datasets into clean, reliable information
• Build and refine dimensional data models, such as star schemas, to enable robust reporting and analytics
• Write and optimize scripts, processes, and jobs to streamline data operations and remove bottlenecks
• Explore new tools, frameworks, and real‑time processing technologies to keep the data platform current
• Champion best practices in coding, documentation, and technical quality
• Ensure data quality, accuracy, and availability through validation, monitoring, and governance processes

Requirements

• Strong SQL expertise and hands‑on experience with relational databases such as SQL Server, MySQL, Vertica, and others
• Experience integrating and consuming APIs
• Ability to leverage AI tooling as part of solution development
• Practical experience with data warehousing and dimensional modeling for large‑scale systems
• Proficiency in Python programming
• Familiarity with distributed systems (Kafka, Spark, Iceberg) and NoSQL/document stores (MongoDB)
• Know-how with ETL orchestration tools (Airflow, Luigi) and visualization platforms (Power BI, Tableau, Looker, SSRS)
• Excellent communication skills to translate complex data solutions into business value
• Background in energy solar and storage is a plus, but curiosity and a problem‑solving mindset matter most

Technologies

• SQL
• SQL Server
• MySQL
• Vertica
• APIs
• Python
• Kafka
• Spark
• Iceberg
• MongoDB
• Airflow
• Luigi
• Power BI
• Tableau
• Looker
• SSRS