Senior Data Engineer

Overview

Who we are

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 team in the Supply Chain group is seeking multiple talented Senior Data Engineers to join our development team. This role will focus on implementing and maintaining high-quality data engineering solutions while collaborating with senior team members to deliver value to our customers.

Reporting to the Senior Manager, Digital Innovations, the person in this role will support the Supply Chain transformation objectives and help accelerate the adoption of modern and emerging technologies and 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 you should expect to move between teams and across different parts of the supply chain as those priorities shift.

• Implementing technical solutions that align with architectural decisions and enterprise standards.
• Designing, developing, and maintaining scalable data pipelines using Python, Databricks, and Apache Airflow / AWS Step Functions.
• Implementing and optimizing ETL processes to extract, transform, and load data from enterprise sources into product datastores.
• Working with Business Product Owners to refine requirements and acceptance criteria.
• Applying data quality and validation techniques to ensure accuracy and reliability of datasets.
• Troubleshooting and resolving data-related issues to ensure smooth project execution.
• Collaborating with cross-functional teams to integrate data engineering solutions into the product framework.
• Ensuring non-functional requirements — security, performance, scalability, and system integrations — are met through effective design and development.
• Using AI as an assistant across your daily work — pipeline development, code review, testing, debugging, and documentation — to deliver better outcomes faster, while holding quality and review standards.
• Prototyping and experimenting to answer open questions quickly: build the smallest thing that tests the idea, measure what it shows, and share what you learned — including when it does not work.
• Spending time with the planners, logistics, and operations teams who use what you build, so solutions reflect how the work actually happens.
• Bringing new tools, techniques, and emerging technology into the team's day-to-day practice, and helping teammates adopt what proves out.

• Strong technical expertise in data architecture and data integrations, with 5+ years of hands-on experience with modern technologies.
• 5+ years of proven expertise creating end-to-end data engineering pipelines handling large data volumes to support data science and business analytics.
• 3+ years of hands-on experience with ETL pipelines, Python, and SQL.
• Proficiency in PySpark, Scala-Spark, and scripting languages, with Databricks and AWS Glue expertise.
• Proficient understanding and practical experience with cloud-based Big Data technologies — AWS EMR, Apache Spark, Databricks, AWS Redshift, S3 — and orchestration tools such as Apache Airflow / AWS Step Functions.
• Hands-on experience with technical design, development, conducting code reviews, and driving code quality.
• Experience with log monitoring and error-notification tools such as Datadog / CloudWatch and Grafana.
• Proven experience in cloud engineering, including provisioning AWS services with Terraform and CloudFormation.
• Strong understanding of DevOps practices, CI/CD pipelines, agile methodologies, and version control systems (Git).
• Proven ability to work through technical challenges and complex problem-solving to deliver high-quality products, digging to root cause rather than treating symptoms and understanding the business problem before reaching for a solution.
• Experience with both functional and non-functional requirements, including security, performance, and scalability.
• Excellent communication skills, with the ability to collaborate effectively across cross-functional teams.
• Demonstrated use of AI tools as an assistant in your engineering workflow, with the judgment to know where they help, where they do not, and how to keep quality and review standards intact.
• Curiosity about emerging technology and a willingness to experiment — trying new tools and approaches, learning quickly from what does not work, and sharing what you find with the team.
• Comfort working as part of a cross-functional fusion team and moving across different parts of the supply chain as priorities change.

• Java and Java-streaming development for real-time / near-real-time processing and event-driven architectures.
• Experience building AI/ML data pipelines, feature-engineering workflows, and scalable data products for model development.
• Experience preparing structured and unstructured data for model training, inference, and automation use cases.
• Familiarity with AI concepts — machine learning, generative AI, prompt engineering, model evaluation, AI governance — and responsible-AI considerations.
• Experience using GitHub Copilot within secure development workflows while maintaining code quality and review standards.
• Demonstrated experience transforming large-scale applications.
• AWS Certified Developer (Associate) or equivalent cloud certifications.
• Supply chain experience.
• Experience building with LLMs or AI agents in production data and application workflows — retrieval, tool calling, evaluation, or agentic pipelines.

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.

Have a question, need assistance with your application or do you require any special accommodations? Please send an email to [email protected].