Senior Data Engineer

Description:
We are looking for a hands-on Senior Data Engineer to help build and evolve Tesla’s next-generation enterprise analytics platform that powers business intelligence, operational intelligence, manufacturing insights, supply chain visibility, service telemetry, energy operations, 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 vehicle production, global delivery, battery lifecycle, Supercharger network, Full Self-Driving development, and energy grid optimization.

Responsibilities:
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 and implement 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 platform health – 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

Requirements:
Extensive years of professional experience as a Data Engineer, Backend Engineer, or ETL developer building large-scale data platforms
Skilled with SQL, Python for data engineering (pandas, PySpark, 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
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
Experience with containerization (Docker) and orchestration (Kubernetes / ECS) is required
Excellent communication skills. Able to explain technical trade-offs to engineers and business value to non-technical stakeholders