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.
To save time applying, Toyota does not offer sponsorship of job applicants for employment-based visas or any other work authorization for this position at this time.

WHO WE’RE LOOKING FOR

Toyota’s Data Department is looking for a passionate and highly motivated Data Engineer. The primary responsibility of this role is to develop and maintain scalable cloud infrastructure solutions for data platforms and build data engineering pipelines to support analytics and reporting needs. Reporting to the Data Engineering Manager, the person in this role will support the OneTech Data department’s objective to build state of the art Data Platforms and develop Data Products in support of various Analytical needs across the organization.

• Develop, and maintain scalable, secure, and cost-optimized cloud infrastructure for Data Lake, Data Warehouse, and analytics platforms using Infrastructure as Code (IaC) tools such as Terraform, AWS CloudFormation, or equivalent.
• Develop automations for provisioning, configuration, and deployment of cloud resources (e.g., AWS S3, Redshift, Databricks, Sagemaker, EMR, Lambda, EC2, SNS, Elastic Cache) to support data engineering workloads.
• Build and maintain CI/CD pipelines for data platform components and data engineering workflows using Jenkins, Ansible, Chef, XL Release, XL Deploy, or similar tools.
• Monitor system performance, troubleshoot incidents, and implement continuous improvements to enhance platform reliability and scalability.
• Build and maintain platform health checks, monitoring, alerting, and resiliency mechanisms to ensure high availability and performance of data systems.
• Develop, and maintain end-to-end data engineering pipelines using Apache Spark, Scala, Databricks, and Informatica ETL tools to ingest, transform, and load large-scale datasets.
• Develop automation frameworks for pipeline testing, validation & Observability solutions to track data quality, timeliness, and accuracy.
• Stay current with emerging technologies, industry trends, and competitive product stacks to recommend innovative solutions and maintain a competitive edge.
• Document technical designs, operational procedures, and best practices to facilitate knowledge sharing and team onboarding.