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Mid-level generalist backend/platform role, metro location, and broad common skillset increase applicant competition.
Core backend, API, and cloud platform skills are broadly transferable across industries.
Explicit 5–8 year requirement plus mandatory backend, cloud, and Kubernetes skills.
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Design, build, and optimize secure, scalable, high-performance REST/gRPC/GraphQL APIs and event-driven microservices that expose curated data from enterprise systems, IoT devices, and analytical models.
Collaborate with Data Engineering teams to deliver reliable, observable, production-ready data services enabling real-time insights, predictive analytics, and digital twin workflows.
Manage API lifecycle including versioning, monitoring, observability, and deploy services using Docker, Kubernetes, and cloud-native platforms (AWS/Azure).
5–8 years professional software engineering experience.
Bachelor's or Master's degree in Computer Science, Engineering, or related technical field.
Strong experience in API development (REST, gRPC, GraphQL), microservices architecture, and distributed systems.
Proficiency with backend programming languages (Java with Spring Boot, Python), cloud platforms (AWS/Azure), container orchestration (Docker/Kubernetes), and CI/CD pipelines.
Experienced individual contributor comfortable with hands-on software engineering in platform and services development.
Proven ability to optimize microservices for scalability, high availability, and low latency in industrial IoT or manufacturing data environments.
Collaborates effectively with cross-functional teams, especially Data Engineering, to ensure secure, compliant, and production-grade data services aligned to digital manufacturing platform strategy.