Platform Software 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.

Do you believe data tells the real story? We do! Redefining mobility requires quality data, metrics, and analytics, as well as insightful interpreters and analysts. That's where Global Data Insight & Analytics makes an impact. We advise leadership on business conditions, customer needs and the competitive landscape. With our support, key decision makers can act in meaningful, positive ways. Join us and use your data expertise and analytical skills to drive evidence-based, timely decision making.

Do you believe data tells the real story? We do! Redefining mobility requires quality data, metrics, and analytics, as well as insightful interpreters and analysts. That's where Global Data Insight & Analytics makes an impact. We advise leadership on business conditions, customer needs and the competitive landscape. With our support, key decision makers can act in meaningful, positive ways. Join us and use your data expertise and analytical skills to drive evidence-based, timely decision making.

Note, this is a hybrid position whereby the employee will work both from home and from the anticipated worksite. Hence, the employee must live within a reasonable commuting distance from the anticipated worksite. This position involves Design and Build Data Pipelines:
Architect, develop, and maintain scalable data pipelines and microservices that support real-time and batch processing on GCP. Service-Oriented Architecture (SOA) and Microservices:
Design and implement SOA and microservices-based architectures to ensure modular, flexible, and maintainable data solutions. Full-Stack Integration:
Leverage your full-stack expertise to contribute to the seamless integration of front-end and back-end components, ensuring robust data access and UI-driven data exploration. Data Ingestion and Integration:
Lead the ingestion and integration of data from various sources into the data platform, ensuring data is standardized and optimized for analytics. GCP Data Solutions:
Utilize GCP services (Big Query, Dataflow, Pub/Sub, Cloud Functions, etc.) to build and manage data platforms that meet business needs. Data Governance and Security:
Implement and manage data governance, access controls, and security best practices while leveraging GCP's native row- and column-level security features. Performance Optimization:
Continuously monitor and improve the performance, scalability, and efficiency of data pipelines and storage solutions. Collaboration and Best Practices:
Work closely with data architects, software engineers, and cross-functional teams to define best practices, design patterns, and frameworks for cloud data engineering. Automation and Reliability:
Automate data platform processes to enhance reliability, reduce manual intervention, and improve operational efficiency.

What you'll be able to do:

Platform Software 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 anticipated worksite. Hence, the employee must live within a reasonable commuting distance from the anticipated worksite. This position involves Design and Build Data Pipelines:
Architect, develop, and maintain scalable data pipelines and microservices that support real-time and batch processing on GCP. Service-Oriented Architecture (SOA) and Microservices:
Design and implement SOA and microservices-based architectures to ensure modular, flexible, and maintainable data solutions. Full-Stack Integration:
Leverage your full-stack expertise to contribute to the seamless integration of front-end and back-end components, ensuring robust data access and UI-driven data exploration. Data Ingestion and Integration:
Lead the ingestion and integration of data from various sources into the data platform, ensuring data is standardized and optimized for analytics. GCP Data Solutions:
Utilize GCP services (Big Query, Dataflow, Pub/Sub, Cloud Functions, etc.) to build and manage data platforms that meet business needs. Data Governance and Security:
Implement and manage data governance, access controls, and security best practices while leveraging GCP's native row- and column-level security features. Performance Optimization:
Continuously monitor and improve the performance, scalability, and efficiency of data pipelines and storage solutions. Collaboration and Best Practices:
Work closely with data architects, software engineers, and cross-functional teams to define best practices, design patterns, and frameworks for cloud data engineering. Automation and Reliability:
Automate data platform processes to enhance reliability, reduce manual…