Kyle Michael

10+ Experienced .NET Full Stack Engineer with a background in building scalable systems for healthcare, veterinary services, and eCommerce industries. Expert in C#, ASP.NET Core, JavaScript, Python, Java, Angular, React, AWS, and Azure cloud platforms. Adept at applying Agile methodologies to deliver high-quality software on time, with strong problem-solving abilities and effective communication in cross-functional teams.

Senior.Net Full Stack Engineer / Solutions Architect at Relias (2022-09 – Present)

• Architected scalable ASP.NET Core 8 applications integrated with SQL Server 2019 databases, resulting in a 15% reduction in patient data retrieval times and improved healthcare provider efficiency across multiple hospital management systems.
• Implemented robust ASP.NET MVC architectures utilizing Entity Framework for efficient medical record access, leading to a 12% increase in application responsiveness and streamlined patient care processes in busy clinical environments.
• Orchestrated the migration of legacy healthcare systems to modern Blazor frameworks, incorporating SQLite for local data storage, enhancing offline capabilities for remote healthcare workers and reducing server load by 18% in distributed medical applications.
• Spearheaded the implementation of comprehensive unit testing strategies using NUnit within healthcare-focused ASP.NET Core 6.0 projects, resulting in a 95% code coverage and significantly reducing errors in critical patient data management systems.
• Integrated MediatR library into multiple microservices to facilitate a clean separation of concerns, resulting in a 15% reduction in code duplication and enhancing overall system maintainability.
• Implemented event-driven architecture using MediatR to handle cross-cutting concerns like logging and validation, reducing manual error handling efforts by 18% across all service components.
• Developed data transformation pipelines using Python 3.10 and Pandas 1.5, streamlining preprocessing of healthcare datasets for ingestion into Azure Cosmos DB, improving consistency and reducing ingestion errors by 22%.
• Developed machine learning models with Python and Pandas to automate healthcare data preprocessing, improving data consistency and reducing ingestion errors by 22% before moving datasets into Azure Cosmos DB for efficient storage.
• Engineered a predictive healthcare analytics engine using Java and Spring Boot, analyzing patient data to reduce diagnostic errors by 18% and improving decision-making capabilities for healthcare providers.
• Revamped Java Spring Boot microservices to efficiently handle high-volume patient data, ensuring seamless scalability and significantly reducing error rates in complex healthcare data processing workflows.
• Designed an intelligent recommendation engine using Java Spring MVC and JPA, enhancing personalized product suggestions, improving customer engagement, and boosting retention rates by 16%.
• Redesigned medical pages using RxJS and Angular Material, reducing API response times by 16%, improving real-time medical records updates, and enhancing performance during high-traffic healthcare data.
• Enhanced state management applications using NgRx and Angular CLI, optimizing patient care workflows, improving data synchronization, and reducing load times for high-demand healthcare services.
• Developed dynamic pricing components using Angular Universal and Angular API Management, ensuring fast server-side rendering, optimizing SEO rankings, and improving performance on dynamic medical pages.
• Implemented and executed automated tests for Angular 12+ healthcare platforms with Jest and RxJS, achieving 98% test coverage, reducing deployment rollbacks by 12%, and ensuring reliable system stability.
• Optimized React-based medical interfaces using Next.js and React Query, improving page load speeds by 14%, enhancing dynamic content rendering, and ensuring a seamless patient experience for users.
• Developed scalable React applications with Redux and Styled Components, ensuring a consistent UI, reducing style conflicts by 18%, and improving component reusability across multiple healthcare platforms.
• Orchestrated the integration of IoT sensors into cloud-based healthcare platforms, optimizing real-time patient data processing and improving response times by 15% during high traffic events in hospital management systems.
• Spearheaded the design of IoT-enabled veterinary tracking systems, leveraging AWS Lambda and DynamoDB to enhance remote medication tracking and ensuring 24/7 access to critical patient data, which reduced data retrieval times by 18%.
• Engineered scalable healthcare backend services using Azure Functions and Azure App Service, improving request processing by 16%, optimizing performance, and ensuring reliability under peak healthcare loads.
• Enhanced medical recommendation engines with Azure Cosmos DB and Azure Monitor, improving data retrieval speeds, boosting personalization accuracy by 12%, and optimizing user experience.
• Developed serverless patient care management workflows using Azure API Management and Azure Functions, automating fulfillment, reducing manual processing errors, and improving operational efficiency.
• Strengthened observability in healthcare platforms with Azure Monitor and Azure App Service, ensuring real-time error detection, minimizing appointment scheduling failures, and improving incident response time.
• Engineered auto-scaling healthcare services using AWS Elastic Beanstalk and AWS Fargate, optimizing infrastructure efficiency and reducing server costs by 12% during peak patient traffic loads.
• Optimized healthcare appointment scheduling workflows using AWS Lambda and AWS DynamoDB, improving transaction reliability, reducing healthcare data processing latency by 18%, and ensuring seamless patient experience.
• Leveraged Apache Kafka and Microservices to implement real-time inventory updates across the eCommerce platform, improving data consistency and reducing order fulfillment delays by 12% during high traffic events.
• Developed a robust messaging layer using RabbitMQ and Microservices, streamlining communication between payment and inventory systems, ensuring high availability and reducing transaction processing time by 10%.
• Integrated Splunk and Datadog for end-to-end monitoring of the eCommerce platform, providing real-time insights into transaction performance and reducing system downtime by 12% during high traffic periods.
• Utilized Prometheus and Grafana to implement a comprehensive monitoring solution for the eCommerce backend, improving system observability and alerting, which led to a 15% reduction in critical downtime incidents.
• Managed cloud infrastructure using Terraform and Kubernetes, improving service reliability by automating resource provisioning and achieving seamless scaling for distributed system applications.
• Integrated Spinnaker and Jenkins to create continuous deployment workflows for a distributed microservices architecture, enabling fast, reliable, and repeatable deployments with minimal downtime.

Senior.NET Engineer / Platform Engineer at Chewy (2017-03 – 2022-08)

Bachelor's Degree in Computer Science – University of Florida (2009-09 – 2014-04)