At Verizon, we contributed to the design and implementation of IoT microservices supporting connected device ecosystems and real-time data streaming. The project began with planning edge data processing requirements and architecting a scalable system using Golang, Kafka, and Apache Spark for high-throughput stream processing. Redshift was used to build robust data pipelines for analytics and reporting. APIs were managed through Apigee, ensuring secure and efficient communication across distributed services. Rigorous testing validated microservice performance, data accuracy, and system reliability. CI/CD pipelines were implemented using Jenkins, Kubernetes, and Helm to enable seamless deployment and orchestration across cloud-native environments. Post-deployment monitoring and visualization were achieved through interactive dashboards, providing real-time insights into system health, data flow, and user engagement. This end-to-end solution empowered Verizon’s consumer platforms with scalable, event-driven architecture and actionable analytics, enabling personalized digital experiences and improved operational efficiency across its IoT ecosystem.