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Stanley Johnson

@stanleyjohnson

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Software Engineer at Deloitte Ireland who modernised agriculture inspections with Java, Quarkus, and microservices.

Ireland

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At Deloitte Ireland, I built Java and Quarkus REST APIs for the Smart Logbook Service, modernising legacy inspection data for the Department of Agriculture. I also implemented ActiveMQ messaging and secured service access with Keycloak and JWT.

At Capgemini, I developed Spring Boot services and Angular components for a life insurance platform, improving policy workflows and data processing. I also built a personal healthcare event streaming project with Kafka, PostgreSQL, Spring Security, and HL7 FHIR.

Experience

Work history, roles, and key accomplishments

Current

Professional Development and Independent Projects

Current

Self Employed

Aug 2025 - Present (1 year 2 months)

Focused on backend engineering depth including event-driven systems with Apache Kafka, Spring Boot 3, containerisation with Docker, and hands-on cloud platform work. Built a healthcare event streaming system as a personal project.

Kafka Spring Boot 3 Docker PostgreSQL Spring Security HL7 FHIR System Design

Software Engineer (Solutions Engineer)

Deloitte Ireland

Jan 2025 - Jul 2025 (6 months)

Built REST APIs in Java and Quarkus for the Smart Logbook Service, a microservices platform modernising legacy inspection data. Implemented event-driven communication using ActiveMQ and integrated Keycloak and JWT authentication.

Java Quarkus REST APIs ActiveMQ Oracle SQL Keycloak JWT Jenkins Maven OpenShift JUnit5 Mockito JaCoCo SonarQube Nexus Test Driven Development

Software Engineer

Capgemini

Jul 2021 - Aug 2023 (2 years 1 month)

Developed Spring Boot backend services and REST APIs for a life insurance e-application platform. Built Angular front-end components with reactive forms and designed XML to JSON transformation pipelines.

Java Spring Boot REST APIs Angular Reactive Forms XML JSON Oracle SQL Junit Mockito Agile

Machine Learning Engineer (Internship)

The Sparks Foundation

Jan 2020 - May 2020 (4 months)

Designed and implemented two machine learning based recommendation models in Python, applying feature engineering, model tuning and performance monitoring. Collaborated with data engineering teams to operationalise the models end to end.

Python Machine Learning Feature Engineering & Model Tuning data preprocessing Deployment