Gregory Alway
Senior Full Stack Java Engineer / Tech Lead
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About
As a Java Full Stack Engineer with over 11 years of experience, I specialize in designing and implementing comprehensive solutions that contribute to business growth. My core expertise includes Java 16/17, Spring Framework, and creating RESTful APIs for seamless system integration. I am proficient in modern frontend technologies such as Angular 15, React 18, and Vue.js 3, utilizing TypeScript and JavaScript to build engaging user interfaces.
With extensive experience in database management, I focus on building scalable and high-performance applications. My background includes significant projects in healthcare and financial sectors, where I have demonstrated strong cloud experience with Azure and AWS. By incorporating cloud solutions, I build, deploy, manage, and optimize applications effectively.
This expertise supports the creation of scalable, reliable cloud-based applications that align with modern software development practices. I thrive in collaborative Agile teams, mentor junior developers, and continuously advance my technical skills to stay ahead of industry trends.
Experience
- Led the migration of Infor's Landmark platform from on-premise infrastructure to AWS, leveraging EKS (Elastic Kubernetes Service), Docker, and AWS Fargate, achieving a 30% reduction in operational costs and improved scalability.
- Utilized Java 17, Spring Boot 3, and AWS services such as Lambda, S3, EC2, RDS, and DynamoDB to build scalable, multi-tenant, and single-tenant financial systems.
- Designed and deployed microservices using Spring Boot 3 and OpenAPI 3.0, ensuring compatibility with AWS environments and Dockerized containers for financial data processing.
- Optimized application performance with MongoDB 5, reducing data access latency by 25% for high-speed financial transactions.
- Re-architected core components of the Landmark Framework with Java 17, Spring Boot 3, and AWS EKS to support high-volume financial transactions with enhanced scalability and compliance.
- Designed backend components using Spring Data JPA and MongoDB 5, streamlining data replication and logging frameworks for multi-tenant environments.
- Collaborated with UI teams to integrate Angular 16 with NgRx, React 18 with Redux, and Vue.js 3 with Vuex, connecting front-end applications with backend services via RESTful APIs to enable real-time responsiveness.
- Integrated AWS S3 for high-availability document storage, optimized for large-scale financial document retrieval.
- Conducted system-wide performance optimizations using Java 17, Spring Boot 3, EKS, and Docker to enhance reliability during peak transaction periods.
- Improved concurrency handling for payroll and financial transactions across tenants, reducing transaction times by 20% and eliminating peak downtime.
- Implemented algorithms in Java 17 to handle up to 75,000 concurrent user requests with 15% faster processing speeds.
- Integrated Human Capital Management (HCM) and Financial Management System (FMS) applications with the Landmark Framework using Java 17 and Spring Boot 3.1.
- Designed APIs and microservices for real-time interaction between HR and financial systems, ensuring secure communication with Spring Security 6 and OAuth 2.1.
- Automated deployment processes with GitHub Actions, Jenkins, EKS, and Docker, reducing release times by 60% and increasing deployment frequency.
- Leveraged Kubernetes (EKS) and Terraform for container orchestration and infrastructure as code, ensuring seamless scaling during high transaction loads.
- Enhanced database performance for transactional workloads using PostgreSQL, MySQL, and MongoDB 5, optimizing query execution and indexing strategies.
- Designed and implemented database schemas, ensuring scalability and performance for multi-tenant financial applications with Spring Data JPA and Hibernate ORM.
- Developed automated testing suites with JUnit 5, TestNG, and Cypress, ensuring continuous quality assurance.
- Designed and maintained multi-environment CI/CD pipelines using Jenkins, GitHub Actions, and ArgoCD, enabling automated deployment to Kubernetes (EKS) and AKS clusters with zero downtime.
- Created and managed infrastructure using Terraform and AWS CloudFormation, ensuring consistent, scalable, and reusable infrastructure for cloud deployments.
- Led global compliance testing using JUnit 5 and Selenium, ensuring adherence to GDPR, PCI DSS, and SOX standards.
- Designed secure solutions with AWS IAM, Spring Security, and AWS KMS, ensuring data security for financial operations.
- Built modular components in Angular 16 with NgRx, React 18 with Redux, and Vue.js 3 with Vuex, improving efficiency and maintainability across financial services applications.
- Enhanced user experience by integrating real-time data visualizations with D3.js and Chart.js for actionable financial insights.
- Designed responsive, interactive UIs with Material UI and Bootstrap 5, improving accessibility and cross-device usability.
- Integrated front-end components with backend microservices via GraphQL and REST APIs, ensuring seamless synchronization between UI and backend.
- Conducted team workshops and training on advanced Java, Spring Boot, and cloud-native practices, enhancing team expertise and productivity.
- Designed and deployed scalable AWS Lambda functions to process high-volume data asynchronously, reducing operational costs by 20%.
- Implemented AWS CloudWatch and AWS X-Ray for monitoring and troubleshooting distributed systems, improving system observability.
- Used AWS Glue for ETL pipelines, integrating multiple data sources into a centralized Amazon S3 repository for analytics.
- Migrated critical application workloads to Azure Kubernetes Service (AKS), ensuring cost-efficient scalability and resiliency.
- Designed data pipelines using Azure Data Factory and Azure Blob Storage, improving data integration for financial reporting.
- Implemented secure API management with Azure API Management (APIM), enabling seamless communication across microservices while adhering to compliance standards.
- Developed Python-based machine learning models using scikit-learn and TensorFlow, enabling predictive analytics for financial data and enhancing decision-making processes.
- Automated operational workflows by creating Python scripts integrated with AWS Lambda and S3, reducing manual intervention by 40%.
- Built AI-driven chatbots using Python, NLTK, and Dialogflow, streamlining customer support interactions and improving response accuracy by 30%.
- Facilitated effective communication and collaboration across cross-functional teams in multiple locations to meet project deadlines and deliver high-quality financial services applications.
- Managed collaboration between onshore and offshore team members using Azure DevOps best practices for consistent deployments in multi-tenant environments.
- Mentored junior developers, providing technical guidance and fostering their professional growth through code reviews, pair programming, and knowledge-sharing sessions by using MS Teams, Jira and Slack.
Education
Bachelors degree in computer science at University of South Florida

