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# Data Engineer

- **Company:** Tesla, Inc.
- **Location:** Austin, TX, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Airflow, Automated Storage and Retrieval Systems, Code Review, Continuous Integration, Data Architecture, Data Transmissions, Information Engineering, Extract Transform Load (ETL), Python (Programming Language), NoSQL, Query Optimization, Power BI, Standard Sql, Software Engineering, SQL Databases, Tableau (Software), WebSocket, Data Processing, ReactJS, Grafana, Apache Spark, Generative AI, Backend, Git, Kubernetes, Information Technology, Apache Kafka, Front End Software Development, Restful APIs, Streamlit Framework, Data Pipelines
- **Published:** September 25, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=464f070dcc86c2c0

## About the Role

* Degree in Computer Science, Data Engineering, Data Science, Statistics, or an engineering discipline, or equivalent experience
 * 2+ years of experience in data engineering, software engineering, or a related field
 * Proficiency in Python and SQL
 * Experience building and operating production ETL pipelines with Apache Airflow or an equivalent orchestration tool
 * Experience in full-stack application development, including backend services and frontend interfaces, preferably with React
 * Hands-on experience developing AI agents and retrieval-augmented generation (RAG) systems, including tool calling, orchestration, embeddings, vector stores, and evaluation of output quality
 * Experience building analytical dashboards using Streamlit, Grafana, Tableau, Power BI, or similar tools
 * Experience with Git, code review, and CI/CD
 * Experience with multiple data architecture paradigms (SQL, NoSQL, Kafka, Spark) and data communication protocols (REST, WebSocket)
 * Experience deploying and operating production services on Kubernetes

## Description

* Design, build, and maintain scalable data pipeline architecture, and advance the automation and standardization of ETL/ELT processes
 * Identify, design, and implement process improvements, including automation of manual workflows, query optimization, and infrastructure redesign for reliability and scale
 * Design and develop full-stack web applications for defect analysis and investigation, including backend services, REST APIs, access control, and frontend interfaces
 * Develop AI agents and retrieval systems that automate quality workflows and generate preliminary root-cause investigations for engineering review
 * Evaluate agent performance for accuracy, groundedness, and appropriate handoff to engineering review
 * Create visualizations, dashboards, and reports using Tableau, React, or Grafana to monitor key metrics and support decision-making
 * Conduct end-to-end analyses, from requirements gathering through data processing, modeling, statistical analysis, and root-cause investigation of system and metric changes


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