Senior Engineer - Data Engineering

Toyota North America•Plano, TX

7d•Onsite

About The Position

Toyota's Digital Innovations team in the Supply Chain group is hiring Senior Data Engineers to implement and maintain high-quality data engineering solutions in support of Supply Chain transformation. The role works with senior team members to deliver value to customers and reports to the Senior Manager, Digital Innovations. The position is based at Toyota Motor North America Headquarters in Plano, Texas. The engineer works in a cross-functional fusion team of engineers, product staff, and supply chain operators who share goals and a backlog. Team assignments may change across teams and parts of the supply chain as priorities shift. The role involves developing scalable pipelines and ETL solutions, maintaining data quality, and meeting security, performance, scalability, and integration needs. It also includes prototyping ideas, using AI tools as an engineering assistant while maintaining quality and review standards, and engaging directly with the planners, logistics, and operations teams who use the solutions.

Requirements

At least 5 years of hands-on experience with modern data architecture and data integration technologies.
At least 5 years of experience creating end-to-end data engineering pipelines for large data volumes supporting data science and business analytics.
At least 3 years of hands-on experience with ETL pipelines, Python, and SQL.
Proficiency in PySpark, Scala-Spark, and scripting languages, with expertise in Databricks and AWS Glue.
Practical experience with cloud-based big data technologies including AWS EMR, Apache Spark, Databricks, AWS Redshift, and S3, and orchestration tools such as Apache Airflow or AWS Step Functions.
Hands-on experience with technical design and development, conducting code reviews, and driving code quality.
Experience with log monitoring and error-notification tools such as Datadog, CloudWatch, and Grafana.
Cloud engineering experience, including provisioning AWS services with Terraform and CloudFormation.
Strong understanding of DevOps practices, CI/CD pipelines, agile methodologies, and version control systems such as Git.
Ability to solve complex technical challenges, identify root causes, and understand the business problem before selecting a solution.
Experience with functional and non-functional requirements, including security, performance, and scalability.
Excellent communication skills and ability to collaborate across cross-functional teams.
Demonstrated use of AI tools in an engineering workflow, with judgment about their appropriate use and how to maintain quality and review standards.
Curiosity about emerging technology and willingness to experiment, learn from unsuccessful approaches, and share findings.
Comfort working in cross-functional fusion teams and moving across supply chain areas as priorities change.
Must have the right to work in the United States without requiring Toyota immigration-related employment support or sponsorship now or in the future.

Nice To Haves

Java and Java-streaming development for real-time or 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 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) certification or equivalent cloud certifications.
Supply chain experience.
Experience building with LLMs or AI agents in production data and application workflows, including retrieval, tool calling, evaluation, or agentic pipelines.

Responsibilities

Implement technical solutions that align with architectural decisions and enterprise standards.
Design, develop, and maintain scalable data pipelines using Python, Databricks, and Apache Airflow or AWS Step Functions.
Implement and optimize ETL processes to extract, transform, and load data from enterprise sources into product datastores.
Work with Business Product Owners to refine requirements and acceptance criteria.
Apply data quality and validation techniques to ensure dataset accuracy and reliability.
Troubleshoot and resolve data-related issues.
Collaborate with cross-functional teams to integrate data engineering solutions into product frameworks.
Ensure security, performance, scalability, and system-integration requirements are met through effective design and development.
Use AI as an assistant for pipeline development, code review, testing, debugging, and documentation while maintaining quality and review standards.
Prototype and experiment to test ideas, measure results, and share findings, including unsuccessful outcomes.
Spend time with planners, logistics, and operations teams to ensure solutions reflect their work.
Bring new tools, techniques, and emerging technology into team practices and help teammates adopt effective approaches.

Benefits

Professional growth and development programs.
Tuition reimbursement.
Team Member Vehicle Purchase Discount.
Toyota Team Member Lease Vehicle Program, if applicable.
Comprehensive health care and wellness plans for the employee's entire family.
Toyota 401(k) Savings Plan with a company match and annual retirement contribution, if applicable.
Paid holidays and paid time off.
Referral services related to prenatal services, adoption, childcare, schools, and more.
Tax-advantaged accounts, including Health Savings Account, Health Care FSA, and Dependent Care FSA.
Relocation assistance, if applicable.