Tesla

Makes electric cars, robotaxis and grid batteries

Senior Data Engineer - Optimus

Data EngineeringConfirmed live in the last 24 hours

Full-timeFremont, CA, USANo salary listedIn-person

About the Job

Requirements

A degree in Computer Science, Data Engineering, or Information Systems, or equivalent experience.
At least 4 years of experience in data engineering, preferably supporting manufacturing, operations, or industrial analytics.
Strong expertise in SQL and experience with multiple database platforms, such as MySQL, Microsoft SQL Server, Oracle, Vertica, or ClickHouse.
Proficiency in Python for data engineering and automation, with 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 such as Airflow, Prefect, or Luigi.
A solid understanding of data warehousing concepts, dimensional modeling, and schema design.
Familiarity with containerized and cloud-based deployment using Docker, Kubernetes, AWS, GCP, or Azure.
Experience with BI and visualization tools such as Tableau, Power BI, or Superset.
Strong communication skills and ability to collaborate across engineering and business functions.

Responsibilities

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 the 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 SI resources into streamlined data analysis to enhance efficiency and accuracy in manufacturing operations.

Desired Qualifications

Experience supporting manufacturing, operations, or industrial analytics.

Category	Manufacturing
Location	Fremont, California
Requisition ID	261277
Type	Full-time

Job Description

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.

Job Responsibilities

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 SI resources into streamlined data analysis, enhancing efficiency and accuracy in manufacturing operations

Job Requirements

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

About the Company

Tesla

Makes electric cars, robotaxis and grid batteries

Tesla makes electric cars and batteries that store power for homes and utilities, and it develops self-driving software and humanoid robots. In 2023, its Model Y became the first electric vehicle to rank as the world's best-selling car. Buyers order the Model 3 sedan, Model Y SUV, or Cybertruck pickup directly from Tesla instead of through dealers, and they charge on its Supercharger fast-charging network. It also sells Megapack and Powerwall batteries, runs a robotaxi service, and charges drivers a monthly fee for self-driving software that still needs their supervision. Tesla was founded in 2003, with Elon Musk as its lead early investor and a recognized co-founder, and it is based in Austin, Texas.

Company size: 10,001+
Company stage: IPO
Headquarters: Austin, TX
Founded: 2003

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