Java/Python Software Engineer - Data Platform

Title: Java/Python Software Engineer - Data PlatformLocation: Dearborn, MIDuration: Long TermSkills : Backend: Java, Spring Boot, REST APIsData Pipeline: GCP Dataflow, Apache Beam, BigQuery, GCSDevOps & Cloud: Kubernetes (GKE), Tekton, Docker, Cloud RunPosition Description:The Connected Vehicle Data Enablement (CVDE) organization within Global Data Insight and Analytics (GDIA) builds the data platforms and software capabilities that help Ford teams transform connected vehicle data into actionable insights. Our work supports engineering, product quality, and analytics at scale through reliable, secure, and maintainable data platform solutions. We are looking for a Senior Software Engineer - Data Platform with strong Java and Python experience to help design, build, and evolve production-grade data and automation solutions. This role is ideal for an engineer who combines strong software engineering fundamentals with practical experience delivering cloud-based data platform capabilities. The right candidate will be able to lead through technical depth, mentor peers, work through ambiguity, and remain highly hands-on in delivery, spending approximately 70-90% of their time writing code and building solutions. Role Overview You will work on a small, cross-functional team responsible for building and improving software systems, data transformation pipelines, and platform capabilities that support connected vehicle analytics and engineering use cases. You will partner closely with product managers, business stakeholders, and engineers to translate complex problems into practical, scalable technical solutions. This is a hands-on engineering role with meaningful ownership across architecture, implementation, and delivery.Skills Required:Spring Boot, Python, Google Cloud Platform, SQLSkills Preferred:GCP Cloud Run, Angular, Spring Boot, Big Query, AIPGEEExperience Required:- 6+ years of software engineering experience, including significant experience building cloud-based data platforms or data-intensive systems. - Strong hands-on development experience in both Java and Python, including design, implementation, testing, and deployment. - Proven experience architecting and delivering solutions from concept through production support. - Strong understanding of object-oriented design, distributed systems, and modern software engineering practices. - Experience building on public cloud platforms, preferably Google Cloud Platform (GCP). - Experience with cloud and data platform technologies such as BigQuery, Dataproc, Cloud Run, Airflow/Astronomer, or similar tools. - Experience with CI/CD pipelines, automated testing, and modern version control practices. - Experience with Infrastructure as Code, preferably Terraform. - Experience implementing observability practices, including logging, monitoring, alerting, and operational diagnostics for production systems. - Strong communication skills and the ability to work effectively with technical and non-technical stakeholders. - Demonstrated ability to mentor peers and influence engineering direction through day-to-day technical leadership.Experience Preferred:- Experience building data platforms, data-intensive applications, or large-scale transformation pipelines. - Experience in automotive, manufacturing, telemetry, or other large-scale operational data environments. - Experience working in a large global organization with diverse stakeholders and competing priorities. - Experience with backend or full-stack development in support of internal platforms or data products. - Experience using AI or automation tools to improve engineering productivity, code quality, testing, or documentation workflows. - Google Cloud certification.Additional Information :Hybrid Position 4 days a week onsite - Design, build, test, deploy, and support scalable software solutions using both Java and Python. - Lead the design and implementation of reliable, maintainable, and production-ready data platform and transformation capabilities. - Build and enhance cloud-native applications, services, and workflows on Google Cloud Platform. - Contribute hands-on code while also providing technical leadership, architectural guidance, and mentoring to other engineers. - Partner with stakeholders to clarify requirements, decompose complex problems, and deliver iterative value through agile development practices. - Drive engineering quality through strong design, code reviews, testing, CI/CD automation, observability, and operational excellence. - Improve platform reliability, supportability, and scalability through monitoring, logging, alerting, and performance optimization. - Contribute to infrastructure automation and environment consistency using Infrastructure as Code practices, including Terraform. - Balance short-term delivery goals with long-term platform sustainability, reuse, and technical health. - Evaluate and apply modern engineering tools, including AI-assisted development workflows, where they improve speed, quality, and team effectiveness.