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Mid-level, metro location, strong employer brand, and generalist platform skillset increase applicant competition.
Platform backend skills are broadly transferable across industries though manufacturing domain knowledge moderately matters.
Explicit 5–8 years plus mandatory backend, cloud, Kubernetes, and API skills make filters stringent.
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Design, build, and optimize secure, scalable, high-performance APIs and microservices for data-as-a-service within Digital Manufacturing & Supply Chain Platform.
Collaborate with Data Engineering to transform raw/processed data into reliable, production-ready services supporting real-time insights, predictive analytics, and digital twin workflows.
Own deployment, lifecycle management, observability, and security of services using cloud-native technologies (Docker, Kubernetes, AWS/Azure).
Bachelor's or Master's degree in Computer Science, Engineering, or related technical field.
5-8 years of professional software engineering experience.
Proficiency in API development (REST, gRPC, GraphQL), microservices architecture, backend languages Java (Spring Boot) and Python.
Experience with cloud platforms (AWS/Azure), container orchestration (Docker/Kubernetes), messaging systems (Kafka/Event Hubs), and CI/CD pipelines.
Experienced individual contributor at a senior software engineering level (Grade 22) focusing on platform and services development.
Strong technical focus on building scalable, secure, and observable API/microservices environments integrating enterprise and IoT data.
Comfortable working in cross-functional teams with architects and data engineers to align service designs with platform strategy and operational excellence.