Principal Engineer II – Data Engineering

Toyota Motor North America; Plano (TX); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Health care and wellness plans

401(k) with company match

Paid time off

Relocation assistance

Job summary

Toyota Motor North America is seeking a Principal Engineer II, Data Engineering to spearhead the data platform transformation for Supply Chain. You will define technical direction, lead multiple teams, and partner with product, architecture, and business stakeholders on scalable cloud data and AI/ML solutions.

You will mentor engineers, steer architecture decisions, and drive modernization practices across fusion teams to deliver measurable business impact in a complex enterprise setting.

Qualifications

• 8+ years designing and delivering complex enterprise data and software solutions.
• 5+ years cloud-native data architecture on AWS, Databricks, and Azure.
• 5+ years delivering modern data solutions using Python, PySpark, SQL, Databricks, Spark, and AI/ML workflows.

Responsibilities

• Define the technical vision for large-scale supply chain data platforms built on AWS, Databricks, and Azure.
• Lead architecture and design decisions across data products and teams, balancing speed, quality, and cost.
• Provide principal-level technical leadership across the full data solution lifecycle from discovery to deployment.
• Mentor data engineers, leads, and managers to elevate technical excellence.
• Directly lead multiple development teams by setting priorities and coordinating execution.
• Drive disciplined execution through scaled agile delivery practices with clear user stories and criteria.
• Shape strategic priorities into actionable roadmaps for cloud data, analytics, and AI/ML solutions.
• Lead rigorous technical discussions to ensure solutions meet business objectives and governance standards.
• Establish modern engineering practices— DevSecOps, observability, reliability, and high-quality delivery.
• Identify cross-team dependencies and drive alignment across teams and stakeholders.
• Provide senior leadership with visibility into technical direction and delivery health.
• Set standards for AI-assisted engineering with clear review and security expectations.
• Encourage experimentation and prototyping to convert proven approaches into standards.
• Stay close to the operations and ensure architecture reflects real-world usage.
• Promote a culture of accountability, curiosity, and inclusive leadership across engineering.

Skills

Data architecture

Cloud-native data

Python

PySpark

SQL

Databricks

Spark

AI-enabled engineering

DevOps

Leadership

Tools

AWS

Databricks

SageMaker

Bedrock

Kinesis

Kafka

Job description

Overview

Who we are

Collaborative. Respectful. A place to dream and do. These are just a few words that describe what life is like at Toyota. As one of the world’s most admired brands, Toyota is growing and leading the future of mobility through innovative, high-quality solutions designed to enhance lives and delight those we serve. We’re looking for talented team members who want to Dream. Do. Grow. with us.

Toyota does not offer support or sponsorship of job applicants for employment-based visas or any other work authorization for this role now or in the future. You must have the right to work in the United States and not require Toyota support or sponsorship for immigration-related employment (e.g., H-1B, O-1, E-3, H-1B1, TN, F-1 OPT, F-1 STEM OPT, F-1 CPT, ‘job flexibility benefits’ [also known as I-140 or Adjustment of Status portability], etc.) now or in the future. You should not apply for this role if you will require Toyota to assist with immigration support or sponsorship now or in the future.

This position is based out of Toyota Motor North America Headquarters in Plano, TX

Toyota’s Digital Innovations group within TMNA’s Supply Chain organization is seeking a highly experienced Principal Engineer II, Data Engineering to lead the technical strategy and execution of Supply Chain data platform transformation initiatives. This is an engineering leadership role that combines deep technical expertise, architectural leadership, and accountability for delivery across complex data and software portfolios.

As a Principal Engineer, you will set technical direction, lead complex engineering decisions, and guide execution across multiple development teams in alignment with business priorities. While this role is grounded in principal-level technical leadership, it also requires the ability to shape team operating models, influence delivery practices, and step into direct leadership across one or more engineering teams when needed. You will partner with engineering leaders, enterprise architects, product teams, and business stakeholders to deliver scalable data solutions, remove execution barriers, and drive measurable business impact, while advancing AI-enabled delivery capabilities to elevate engineering productivity, accelerate execution, and strengthen solution quality.

This position reports to the Senior Manager, Digital Innovations and plays a critical role in advancing engineering standards, accelerating digital transformation, and scaling delivery excellence across supply chain data platforms.

You will work as part of a fusion team – engineers, product, and supply chain operators working to a shared goal and a shared backlog, rather than a technology group taking requests from a business group. This is how Digital Innovations operates. Engineers are assigned to fusion teams based on priority and need and move between teams and across different parts of the supply chain as those priorities shift; in this role you will help set those teams up to succeed and keep engineering standards consistent as people move.

What you’ll be doing

• Define and advance the technical vision for large-scale supply chain data platforms built on AWS, Databricks, and Azure, ensuring alignment with business priorities, enterprise architecture, and long-term scalability objectives.
• Lead architecture and design decisions across data products and development teams, balancing speed, quality, resiliency, security, maintainability, and cost optimization.
• Provide principal-level technical leadership across the full data solution lifecycle, from discovery and architecture through implementation, deployment, and operational support for big data and AI/ML workloads.
• Mentor data engineers, technical leads, and engineering managers to elevate technical excellence and strengthen engineering capability across the organization.
• When needed, directly lead multiple development teams by setting priorities, coordinating execution, and establishing effective delivery rhythms across parallel workstreams.
• Drive disciplined execution through scaled agile delivery practices – clear user stories, defined acceptance criteria, effective dependency management, risk mitigation, and measurable outcomes across the development lifecycle.
• Work side by side with product, operations, architecture, and platform partners to shape strategic priorities into actionable technical roadmaps and execution plans for cloud data, analytics, and AI/ML solutions.
• Lead rigorous technical discussions and challenge design decisions to ensure solutions meet business objectives, technical feasibility, data governance, and operational excellence standards.
• Establish and champion modern engineering practices – cloud-native architectures, DevSecOps automation, observability, reliability engineering, and high-quality software delivery standards.
• Identify cross-team dependencies and organizational bottlenecks, and drive alignment and decision-making across engineering teams and stakeholder groups.
• Provide senior leadership with clear visibility into technical direction, delivery health, risks, tradeoffs, and key decisions.
• Set the standard for AI-assisted engineering: use AI as an assistant in your own work, and define where and how teams apply it to improve efficiency, quality, and outcomes – with clear expectations for review, security, and code quality.
• Decide what is worth testing and create the room for the team to test it – running time-boxed experiments and prototypes against architecture, tooling, and emerging technology, and turning what proves out into standards.
• Stay close to the operation. Spend time with the supply chain teams who depend on these platforms so architecture and design decisions reflect how the work actually runs.
• Champion a culture of accountability, curiosity, experimentation, continuous learning, technical excellence, and inclusive leadership across the engineering organization.

What you bring

• 8+ years designing and delivering complex enterprise data and software solutions, including large-scale transformation initiatives.
• 5+ years of deep experience with cloud-native data architecture on AWS, Databricks, and Azure, distributed systems, modern integration patterns, and scalable platform design.
• 5+ years delivering modern data solutions using technologies such as Python, PySpark, SQL, Databricks, Apache Spark, AWS Redshift, and streaming frameworks, with contemporary DevOps and platform-engineering practices.
• Demonstrated success setting technical direction, influencing across multiple teams, and partnering effectively with engineering, product, architecture, and business stakeholders.
• Ability to balance technical excellence, delivery outcomes, AI-enabled engineering capabilities, and cost optimization in a complex enterprise environment.
• Demonstrated use of AI as an assistant in your own engineering work, and experience raising that capability across a team – with the judgment to know where it helps, where it does not, and how to hold quality, security, and review standards.
• A track record of digging to root cause on hard, ambiguous problems, and of understanding the business problem before reaching for a solution.
• Experience leading in a cross-functional team model where engineering and operations share one goal, and comfort re-forming teams as priorities move.

Technical Expertise

• Expertise in data architecture, distributed data processing, domain-driven design, and technical decision-making for scalable data platforms.
• Ability to lead complex design discussions spanning cloud-native data architectures, streaming and event-driven systems (Kinesis, Kafka/MSK), data governance, security, observability, reliability, and operational excellence.
• Experience designing and implementing AI/ML solutions – data preparation, model integration, inference workflows, and automation use cases – with familiarity with AWS AI/ML services such as SageMaker and Bedrock.
• Demonstrated ability to incorporate cost-optimization principles into architecture, cloud platform decisions, and engineering delivery.
• Experience integrating data, analytics, and AI/ML capabilities into production-grade enterprise platforms.

Leadership Capabilities

• Experience leading or coordinating multiple software development teams across complex enterprise initiatives.
• Demonstrated ability to mentor senior engineers and technical leads, influence without authority, and step into direct leadership when needed.
• Strong experience aligning roadmaps, managing dependencies, and driving execution across cross-functional stakeholders and shared priorities.
• Ability to lead adoption of AI-enabled delivery capabilities across teams with appropriate standards, governance, and enablement.
• Excellent communication skills, with the ability to articulate technical strategy, tradeoffs, and delivery status to technical and non-technical audiences.

Added bonus if you have

• Experience in globally distributed, high-performing teams and asynchronous delivery environments.
• Experience leading or contributing to large-scale transformation initiatives.
• Experience with supply chain, manufacturing, logistics, or fulfillment platforms at enterprise scale.
• AWS certifications, such as Solutions Architect or Data Analytics Specialty; Databricks certifications.
• SAFe or other agile delivery certifications.
• Experience developing innovative tooling that improves cross-functional productivity and engineering effectiveness.
• Experience building with LLMs, AI agents, or AI-assisted development platforms in production enterprise environments.
• Experience introducing an emerging technology into an enterprise organization – from evaluation and pilot through standards and adoption.

What we’ll bring

During your interview process, our team can fill you in on all the details of our industry-leading benefits and career development opportunities. A few highlights include:

• A work environment built on teamwork, flexibility, and respect
• Professional growth and development programs to help advance your career, as well as tuition reimbursement
• Team Member Vehicle Purchase Discount
• Toyota Team Member Lease Vehicle Program (if applicable)
• Comprehensive health care and wellness plans for your entire family
• Toyota 401(k) Savings Plan featuring a company match, as well as an annual retirement contribution from Toyota regardless of whether you contribute (if applicable)
• Paid holidays and paid time off
• Referral services related to prenatal services, adoption, childcare, schools and more
• Tax Advantaged Accounts (Health Savings Account, Health Care FSA, Dependent Care FSA)
• Relocation assistance (if applicable)

Belonging at Toyota

Our success begins and ends with our people. We embrace all perspectives and value unique human experiences. Respect for all is our North Star.

Applicants for our positions are considered without regard to race, ethnicity, national origin, sex, sexual orientation, gender identity or expression, age, disability, religion, military or veteran status, or any other characteristics protected by law.