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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Full Stack Data Engineer - **Company:** Ford Motor Company - **Location:** Dearborn, MI, United States - **Contract:** Permanent contract - **Skills:** Clean Code Principles, Java (Programming Language), Agile Methodology, Airflow, JIRA, BigQuery, Cloud Computing, Cloud Computing Security, Cloud Database, Cloud Storage, Databases, Computer Engineering, Information Engineering, Data Governance, Data Infrastructure, Data Systems, Software Design Patterns, Data Flow Control, Python (Programming Language), OpenShift, SQL Databases, Data Streaming, Data Ingestion, Spring-boot, Build Server, Information Technology, Google Cloud Functions, Real Time Data, Apache Kafka, Data Management, Terraform, Data Pipelines - **Published:** October 8, 2026 - **Apply:** https://jobs.mitalent.org/job-seeker/job-details/JobCode/413448541 ## About the Role Bachelor's degree or foreign equivalent in Computer Engineering, Electrical Engineering, Information Technology or a related field and 7 years of progressive, post-baccalaureate experience in the job offered or a related occupation. 7 years of experience with the following skill is required: 1. Using Java and Spring Boot to stream and decode connected vehicle data, enabling high-throughput processing and near real-time data availability. 5 years of experience with each of the following skills is required: 1. Utilizing Kafka, PubSub, OpenShift, Cloud Run or Data Flow by using real time streaming technology. 2. Utilizing databases Spanner, PG SQL or BigQuery. 3 years of experience with each of the following skills is required: 1. Utilizing ApacheBeam, SpringBoot, Dataflow, Airflow, BigQuery, Cloud Storage, Cloud Build, or Cloud Run by applying GCP Cloud data implementation projects experience. 2. Utilizing SpringBoot framework to build high volume streaming. 2 years of experience with the following skill is required: 1. Managing large volumes of connected vehicle data for tracking, analysis, and issue resolution using tools including OpenShift, Kafka, or dataflow. 1 year of experience with the following skill is required: 1. Using Jira in Agile environments to streamline task management and sprint tracking, enabling efficient development of high-throughput systems using Java and Spring Boot for connected vehicle data by leveraging Jira's collaboration and reporting features to support team productivity, transparency, and near real-time data availability., Bachelor's degree or foreign equivalent in Computer Engineering, Electrical Engineering, Information Technology or a related field and 7 years of progressive, post-baccalaureate experience in the job offered or a related occupation. 7 years of experience with the following skill is required: 1. Using Java and Spring Boot to stream and decode connected vehicle data, enabling high-throughput processing and near real-time data availability. 5 years of experience with each of the following skills is required: 1. Utilizing Kafka, PubSub, OpenShift, Cloud Run or Data Flow by using real time streaming technology. 2. Utilizing databases Spanner, PG SQL or BigQuery. 3 years of experience with each of the following skills is required: 1. Utilizing ApacheBeam, SpringBoot, Dataflow, Airflow, BigQuery, Cloud Storage, Cloud Build, or Cloud Run by applying GCP Cloud data implementation projects experience. 2. Utilizing SpringBoot framework to build high volume streaming. 2 years of experience with the following skill is required: 1. Managing large volumes of connected vehicle data for tracking, analysis, and issue resolution using tools including OpenShift, Kafka, or dataflow. 1 year of experience with the following skill is required: 1. Using Jira in Agile environments to streamline task management and sprint tracking, enabling efficient development of high-throughput systems using Java and Spring Boot for connected vehicle data by leveraging Jira's collaboration and reporting features to support team productivity, transparency, and near real-time data availability. ## Description Full Stack Data Engineer - positions offered by Ford Motor Company (Dearborn, Michigan). Note, this is a hybrid position whereby the employee will work both from home and from the aforementioned worksite. Hence, the employee must live within a reasonable commuting distance from the worksite. Design, develop, and maintain scalable data ingestion and curation pipelines from diverse sources, ensuring data is standardized, high-quality, and optimized for analytical use. Leverage Python, SQL, and DBT/Data form to build robust and efficient data pipelines and support seamless end-to-end development, ensuring smooth and reliable data flow from source to insight. Use GCP services (BigQuery, Dataflow, Pub/Sub, and Cloud Functions) to build and manage data platforms that meet and exceed business needs. Implement data governance policies, access controls, and security best practices, utilizing GCP's native security features to protect sensitive data. Employ Astronomer and Terraform for data workflow management and cloud infrastructure provisioning, championing best practices in Infrastructure as Code (IaaC). Continuously monitor and improve the performance, scalability, and efficiency of data pipelines and storage solutions, ensuring optimal resource utilization and cost-effectiveness. Collaborate effectively with data architects, application architects, service owners, and cross-functional teams to define and apply cloud data engineering best practices, design patterns, and frameworks. Automate data platform processes to enhance reliability, improve data quality, minimize manual intervention, and drive operational efficiency. Communicate complex technical decisions to both technical and non-technical stakeholders. Translate complex business requirements into optimized data asset designs and efficient code, ensuring that data solutions directly contribute to business goals. Develop comprehensive documentation for data engineering processes, promoting knowledge sharing, facilitating collaboration, and ensuring long-term system maintainability.