Kevin Phan

Led design of a scalable microservices architecture for large-scale playback and implemented a distributed orchestration service for entitlement checks, session management, and CDN routing. Built high-throughput back-end services in Java (Spring Boot) and Go with Kafka and Apache Flink, applying TDD to improve scalability and resilience under peak traffic. Modernized legacy services to reactive Spring Boot WebFlux with fine-grained authentication and smart routing (Zuul 2, Eureka). Established scalable data and caching strategies with Cassandra, PostgreSQL and Redis, reducing latency. Built real-time observability tooling (React, Apollo, OpenTelemetry) for faster incident detection and MTTR. Enhanced CI/CD with Jenkins and Spinnaker to automate testing and deployments on AWS (EC2, S3) and AWS EKS. Mentored engineers and introduced RFC process to improve design feedback.

Built distributed playback telemetry ingestion processing trillions of events per day from hundreds of millions of devices, enabling near real-time playback health metrics across regions. Implemented AWS Lambda for lightweight event transformation and validation, offloading enrichment from core streaming services to improve elasticity. Developed low-latency gRPC microservices exposing real-time playback metrics to analytics/ML teams, reducing data lag from minutes to seconds. Automated multi-stage telemetry workflows using Netflix Conductor with schema validation, enrichment and aggregation. Designed data models and storage using Cassandra for sub-second queries and S3 for cost-efficient long-term storage. Improved ingestion latency and reliability by applying Resilience4j, tuning JVM GC and thread pools, and using Datadog APM for tracing.

Developed Java (Spring Boot) and Node.js (NestJS) microservices for customer, account and transaction features, supporting real-time digital banking operations and high-volume processing. Implemented event-driven integrations using Kafka and RabbitMQ with RBAC and TLS-encrypted communication to securely synchronize data across banking, analytics and notification systems. Built Angular front-end applications integrated with secure REST and GraphQL APIs, using a modular micro-frontend approach. Contributed to migrating a legacy monolithic system into cloud-based microservices on GCP and Azure. Used GitHub Actions for CI/CD automation and applied DDD and event-sourcing patterns to improve modularity and release speed. Built data ingestion and ETL pipelines in Python using Airflow and Pandas for analytics and fraud-detection workflows. Added schema validation to maintain data integrity and support early anomaly detection. Improved database performance by optimizing Oracle DB indexes, tunin