Data Platform Architect, AI Adoption

Tesla Energy Manufacturing is building the foundational data platforms and governance frameworks that will power AI tools across our global production network, from cell manufacturing and battery assembly to warehousing and logistics operations. We are looking for a Data Platform Architect, AI Adoption to own the architecture, hardware integration, data quality, governance, and stewardship programs that enable clean, accurate, and scalable data across Energy facilities.

In this role, you will design end-to-end data platforms, establish enterprise governance and stewardship standards, architect reliable factory data collection from hardware systems, and ensure high-quality data foundations that the Product Manager, AI Adoption and Forward Deployed Engineers can build upon. You will work closely with software engineers, manufacturing IT/OT teams, and site leadership to create trustworthy, scalable data systems that drive measurable AI impact. This role is for a technical specialist who combines deep architecture and governance expertise with a practical understanding of manufacturing operations and a passion for enabling AI at scale.

Approximately 50% of the role involves travel to Tesla manufacturing sites, where you will provide hands-on support for on-site architecture reviews and system deployments.

• Design and own the reference data platform architecture for Energy Manufacturing AI initiatives, including real-time data ingestion pipelines, lakehouse/warehouse strategy, feature stores, and serving layers optimized for ML and analytics
• Architect hardware and edge data collection strategies: define standards for IoT devices, PLC/SCADA integration, data historians, edge computing, and industrial networking to capture high-fidelity manufacturing data reliably and at scale
• Establish and drive the data governance and stewardship program: create policies for data quality, ownership, lineage, metadata, master data, access controls, and compliance that scale across all Energy sites
• Partner closely with the Product Manager, AI Adoption and Forward Deployed Engineers to translate AI use case requirements, user research findings, and deployment needs into robust data models, pipelines, quality SLAs, and platform capabilities
• Implement data quality frameworks, automated monitoring, validation rules, and remediation processes to guarantee clean, accurate, and timely data for production decision-making and AI models
• Build and maintain platform health, data quality, and governance dashboards and KPIs; use them to drive measurable improvements in data trustworthiness, reliability, and scalability
• Evaluate and select technologies, tools, and vendors for the data ecosystem while aligning with Tesla's first-principles approach and existing infrastructure
• Create scalable deployment playbooks, data onboarding standards, and governance guardrails so new AI tools and sites can adopt the platform rapidly and consistently
• Travel to manufacturing sites to assess current data architecture, support hardware and platform deployments, troubleshoot complex data issues during ramps, and gather first-hand requirements from the factory floor
• Communicate data platform strategy, governance decisions, roadmap priorities, and performance through clear updates and cross-functional briefings to engineering teams and manufacturing leadership
• Degree in Computer Science, Data Engineering, Electrical/Computer Engineering, or a related technical field, or equivalent experience
• 5+ years of experience in data platform architecture, data engineering, or data governance roles; strong preference for experience in manufacturing, automotive, energy, or other high-volume industrial environments
• Deep expertise in modern data platforms and architectures (data lakes/lakehouses, streaming with Kafka/Flink, Spark, Databricks/Snowflake or equivalent, orchestration, and real-time pipelines)
• Hands-on experience with manufacturing data systems including PLCs, OPC UA, MES, SCADA, IoT/edge computing hardware, time-series databases, and OT/IT convergence
• Proven track record implementing data governance, quality frameworks, stewardship models, data lineage, catalogs, and master data management at enterprise scale
• Strong software and infrastructure skills including Python, SQL, infrastructure-as-code, containerization (Docker/Kubernetes), CI/CD, and cloud platforms
• Excellent collaboration and communication skills and a first-principles mindset with genuine passion for building clean, reliable, scalable data foundations that compound AI value in manufacturing

Benefits

Along with competitive pay, as a full-time Tesla employee, you are eligible for the following benefits at day 1 of hire:

• Medical plans > plan options with $0 payroll deduction
• Family-building, fertility, adoption and surrogacy benefits
• Dental (including orthodontic coverage) and vision plans, both have options with a $0 paycheck contribution
• Company Paid (Health Savings Accounts) HSA Contribution when enrolled in the High-Deductible medical plan with HSA
• Healthcare and Dependent Care Flexible Spending Accounts (FSA)
• 401(k) with employer match, Employee Stock Purchase Plans, and other financial benefits
• Company paid Basic Life, AD&D
• Short-term and long-term disability insurance (90 day waiting period)
• Employee Assistance Program
• Sick and Vacation time (Flex time for salary positions, Accrued hours for Hourly positions), and Paid Holidays
• Back-up childcare and parenting support resources
• Voluntary benefits to include: critical illness, hospital indemnity, accident insurance, theft & legal services, and pet insurance
• Weight Loss and Tobacco Cessation Programs
• Tesla Babies program
• Commuter benefits
• Employee discounts and perks program

Expected Compensation

$120,000 - $180,000/annual salary + cash and stock awards + benefits

Pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. The total compensation package for this position may also include other elements dependent on the position offered. Details of participation in these benefit plans will be provided if an employee receives an offer of employment.