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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Engineer - Data Engineering - **Company:** Digital Innovations, L.L.C. - **Location:** Plano, TX, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Agile Methodology, Artificial Intelligence, Airflow, Amazon Web Services, Amazon S3, Big Data, Cloud Computing, Cloud Engineering, Software Quality, Code Review, Continuous Integration, Data Architecture, Information Engineering, Data Integration, Extract Transform Load (ETL), Software Debugging, DevOps, Python (Programming Language), Machine Learning, Operational Databases, SQL Databases, Unstructured Data, Workflow Management Systems, Datadog, Scripting, Enterprise Software Applications, Real Time Systems, Feature Engineering, GitHub Copilot, Large Language Models, Grafana, Prompt Engineering, Apache Spark, Model Validation, Generative AI, Git, Cloudformation, Event Driven Architecture, Pyspark, AWS Glue, Maintaining Code, Cloudwatch, Terraform, Software Version Control, Data Pipelines, Amazon Elastic Mapreduce (EMR), Amazon Redshift, Databricks - **Published:** August 25, 2026 - **Apply:** https://www.dice.com/job-detail/2245d826-1c66-458e-ba33-e018aabf19d1 ## About the Role * 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. Added bonus if you have * 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. ## Description 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. What you'll be doing * 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. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path) - [What is Software Engineering in the Age of AI?](https://www.wearedevelopers.com/magazine/640-what-is-software-engineering-in-the-age-of-ai) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development)