Full Stack Data Engineer

Ford Motor CompanyDearborn, MI
$85,400 - $166,600

About The Position

We made history and now we work to transform the future – for our customers, our communities and our families. You'll see your work on the road every day, helping people move freely and pursue their dreams. At Ford, you can build more than vehicles. Come build what matters. 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. In this position... As a Full Stack Data Engineer supporting the Connected Vehicle Data Team, you will play a key role in designing, developing, and maintaining applications, services, and data solutions that enable connected vehicle data use cases across the enterprise. This role is ideal for a mid-level engineer who enjoys working across both backend and frontend technologies while building scalable, cloud-native applications. You will leverage modern software engineering practices, cloud platforms, event-driven architectures, and data engineering principles to develop reliable, data-driven solutions.

Requirements

  • Mid-level engineer
  • Enjoys working across both backend and frontend technologies
  • Experience building scalable, cloud-native applications
  • Proficiency in modern software engineering practices
  • Experience with cloud platforms
  • Experience with event-driven architectures
  • Knowledge of data engineering principles

Responsibilities

  • Designing, developing, and maintaining applications, services, and data solutions that enable connected vehicle data use cases across the enterprise.
  • Leveraging modern software engineering practices, cloud platforms, event-driven architectures, and data engineering principles to develop reliable, data-driven solutions.
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