Shim Medrano

Designed and operated Java 21 and Spring Boot services on Kubernetes to support high-volume platform workloads, improving service throughput by 32% under sustained peak traffic. Led migration of event pipelines from managed Kafka clusters to a cloud-based streaming footprint with zero downtime. Built and maintained Kafka connectors and schema governance workflows for Protobuf-based services, reducing contract-breaking changes by 40% across multi-team integrations. Implemented Terraform modules for multi-environment infrastructure, standardizing deployment, IAM, networking, and observability patterns across backend teams. Improved operational visibility with DataDog dashboards, Prometheus metrics, and PagerDuty alert tuning, cutting mean time to detect incidents by 35%. Used AI agents to scaffold migration scripts and test fixtures while validating outputs against production constraints and platform standards. Mentored engineers on streaming architecture, API design, and incident respon

Led frontend-heavy development using React and TypeScript, delivering scalable user-facing applications with high performance. Designed and implemented backend services using Python and Node.js to support frontend workflows. Built real-time, data-driven interfaces and deployed the apps on AWS, improving system scalability and reliability. Contributed to system architecture decisions across frontend and backend components and integrated testing and QA practices to improve release quality in remote Agile environments.

Built distributed backend services in Java and Spring Boot to process real-time booking and traveler events across multiple domains, supporting billions of messages per month. Developed Kafka-first integration services and stream processors for event enrichment, routing, and retry handling, improving downstream delivery reliability by 28%. Introduced Protobuf-based message contracts and versioning practices that simplified multi-language service integration and reduced serialization issues in production. Designed cloud-native APIs and asynchronous workflows on AWS using S3, DynamoDB, and containerized services, enabling more resilient and scalable data pipelines. Led a multi-quarter modernization effort replacing legacy queue-based workflows with Kafka-backed services, improving fault tolerance and recovery time during incidents. Strengthened CI/CD and release safety with automated integration tests, canary deployment checks, and better rollback procedures for streaming services.