Sr. Staff Data Engineer, IT Applications

What to Expect

We are looking for a hands-on Sr. Staff Data Engineer to help build and evolve Tesla’s next-generation enterprise analytics platform that powers business intelligence and operational intelligence for Vehicle and Optimus Service and more, all while operating under strict SOX compliance and change management controls. You will design, develop, and operate large-scale data infrastructure in a fast-paced, high-impact environment where decisions affect Service operations and customer experience.

What You’ll Do

• Architect, build, and maintain state-of-the-art Enterprise Data Warehouse / Lakehouse solutions that serve both batch and near-real-time analytics use cases
• Design robust ETL / ELT pipelines using Python and Apache Airflow (or modern orchestration equivalents)
• Develop and operate real-time data streaming and processing platforms using open-source technologies such as Apache Kafka, Apache Spark Streaming / Structured Streaming, Flink, or equivalent
• Maintain platforms– Vertica, SQL Server, Airflow, Tableau etc
• Handle sensitive financial, production, and customer data systems while strictly adhering to SOX controls, segregation of duties, change management, and audit requirements
• Partner closely with business sponsors, product managers, manufacturing engineers, service operations, finance, and IT/security teams to gather requirements, scope projects, and deliver high-quality solutions quickly
• Communicate complex technical concepts and business impact effectively through written documentation, verbal discussions, architecture diagrams, and executive-level presentations (360-degree communication)
• Define, enforce, and continuously improve engineering standards, coding best practices, testing methodologies, CI/CD patterns, monitoring & alerting, and quality assurance processes
• Actively participate in design reviews, code walkthroughs, and pull request reviews across the team
• Stay current with evolving open-source technologies and recommend adoption when they provide meaningful differentiation or operational efficiency

What You’ll Bring

• 8+ years of professional experience as a Data Engineer, Backend Engineer, or ETL developer building large-scale data platforms
• Proficient with SQL, Python for data engineering (pandas, Py Spark, SQLAlchemy, API Scrapping, etc.)
• Strong Proficiency with database systems like Vertica, MySQL, SQL Server, NoSQL, OpenSearch, etc. is required
• Deep hands-on experience designing and operating Airflow DAGs in production at scale
• 3+ years of production experience with at least one distributed streaming system (Kafka, Kafka Streams, Spark Streaming, Flink, Pulsar, etc.)
• Solid understanding of data modeling for analytical workloads
• Experience building and operating systems under SOX compliance or similarly regulated environments (change control, audit trails, separation of duties, etc.)
• Strong SQL skills and understanding of distributed query engines
• 3+ years of experience with containerization (Docker) and orchestration (Kubernetes / ECS) is required
• Excellent communication skills. Be able to explain technical trade-offs to engineers and business value to non-technical stakeholders as well as mentor junior engineers