Full Stack Data Engineer

At Ford Motor Company, we believe freedom of movement drives human progress. We also believe in providing you with the freedom to define and realize your dreams. With our incredible plans for the future of mobility, we have a wide variety of opportunities for you to accelerate your career potential as you help us define tomorrow's transportation.

Enterprise Technology plays a critical part in shaping the future of mobility. If you're looking for the chance to leverage advanced technology to redefine the transportation landscape, enhance the customer experience and improve people's lives, this is the opportunity for you. Join us and challenge your IT expertise and analytical skills to help create vehicles that are as smart as you are.

Enterprise Technology plays a critical part in shaping the future of mobility. If you're looking for the chance to leverage advanced technology to redefine the transportation landscape, enhance the customer experience and improve people's lives, this is the opportunity for you. Join us and challenge your IT expertise and analytical skills to help create vehicles that are as smart as you are.

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.

What you'll be able to do:

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.