Full Stack Software Engineer

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.

About the Role

Join the Connected Vehicle Data Team within Ford's GDIA (Global Data Insight & Analytics) organization to build and transform how we leverage vehicle data across the enterprise. Our team sits at the intersection of massive-scale data engineering, cloud infrastructure, and internal data tools. We build robust data pipelines, scalable backend services, and intuitive data-driven applications that turn complex, high-volume connected vehicle datasets into actionable insights for our business and customers.

In this role, you will not only build the data assets but also embody the Ford OS Behaviors-acting as a Builder who is curious and solves problems, Playing to Win by delivering high-quality data solutions, and Delivering the Promise to our business partners by ensuring data reliability and accessibility.

Are you ready to shape the future of mobility? Join Ford's Connected Vehicle Data Team (GDIA) to build the robust data pipelines, cloud infrastructure, and backend services that transform massive-scale vehicle data into actionable insights. As a curious problem-solver, you will champion Ford OS Behaviors-acting as a Builder, Playing to Win, and Delivering the Promise-to create high-quality, reliable data solutions that empower our enterprise and customers.

What you'll do...

* Build robust data pipelines (Be a Builder):
Design, develop, and maintain scalable ETL/ELT pipelines to ingest, process, and transform large volumes of connected vehicle data using Python, Java, and SQL strictly on Google Cloud Platform (GCP).

* Develop backend services & APIs:
Build RESTful APIs and microservices to expose vehicle data securely and efficiently to internal applications and downstream enterprise systems.

* Develop internal data tools:
Build and maintain lightweight, intuitive frontend interfaces (e.g., React) and dashboards to help stakeholders visualize and interact with complex telemetry data.

* Leverage GCP Data

Infrastructure: Work extensively with GCP data services such as Big Query, Cloud Storage (GCS), Dataflow, or Cloud Composer (Airflow), deploying containerized workloads to Cloud Run or GKE.

* Ensure data quality & reliability (Deliver the Promise):
Implement data validation, automated testing, and monitoring (using Cloud Logging/Monitoring) to ensure high availability and accuracy of our data products.

* Collaborate and innovate (Create Must-Have Products):
Partner closely with Senior Data Engineers, Data Scientists, and Product Managers to understand data models and translate business needs into technical solutions.

What you'll do...

* Build robust data pipelines (Be a Builder):
Design, develop, and maintain scalable ETL/ELT pipelines to ingest, process, and transform large volumes of connected vehicle data using Python, Java, and SQL strictly on Google Cloud Platform (GCP).

* Develop backend services & APIs:
Build RESTful APIs and microservices to expose vehicle data securely and efficiently to internal applications and downstream enterprise systems.

* Develop internal data tools:
Build and maintain lightweight, intuitive frontend interfaces (e.g., React) and dashboards to help stakeholders visualize and interact with complex telemetry data.

* Leverage GCP Data

Infrastructure: Work extensively with GCP data services such as Big Query, Cloud Storage (GCS), Dataflow, or Cloud Composer (Airflow), deploying containerized workloads to Cloud Run or GKE.

* Ensure data quality & reliability (Deliver the Promise):
Implement data validation, automated testing, and monitoring (using Cloud Logging/Monitoring) to ensure high availability and accuracy of our data products.

* Collaborate and innovate (Create Must-Have Products):
Partner closely with Senior Data Engineers, Data Scientists, and Product Managers to understand data models and translate business needs into technical solutions.