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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Fullstack Developer Java/React - **Company:** Insight Global - **Location:** Bentonville, AR, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Java (Programming Language), JavaScript (Programming Language), Unit Testing, Cascading Style Sheets (CSS), Databases, Customer Data Management, Web Development, Distributed Systems, Design of User Interfaces, Apache JMeter, Junit, NoSQL, E2e Testing, Prometheus, Next.js, Responsive Web Design, TypeScript, Performance Testing, ReactJS, Grafana, Spring-boot, Cypress (Programming Language), Data Lakes, Material UI, Apache Kafka, Restful APIs, Jenkins, Microservices - **Published:** August 26, 2026 - **Apply:** https://www.techcareers.com/job.asp?id=3365503551&tx=KP7575FFQ&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54 ## About the Role Strong experience developing applications from scratch Over 6+ years of professional experience as a hands-on Full Stack Developer Strong experience developing on the back end with Java, Spring Boot, NoSQL Database, Kafka and Rest APIs Experience working on microservices and distributed systems Expert in developing Web Applications with React and related technologies Knowledge and practical experience with Storybook component library for efficient UI development and documentation Proficient in JavaScript, React, Next.js, and TypeScript Experience in styling frameworks, including SCSS and CSS, for responsive design Skilled in unit testing with Jest and integration/end-to-end testing with Cypress Experience with telemetry and observability frameworks including Prometheus, Grafana, and ELK Experience with unit and performance testing of applications to increase resilience using technologies including Jenkins, Junit, and JMeter ## Description Our client is looking to hire a Fullstack Developer to help roll out a new initiative for Clinic Intelligence. This project will analyze how internal associates interact with customers in the store. They are building a recommendation platform from scratch that will utilize predictive analytics to make correct recommendations to customers. The platform will generate recommendations from batch components which will run in a data lake and generate recommendations that will populate in a transactional system. SpringBoot applications on the transactional layer will support the front-end. There will be batch applications recurring on the transactional layer and the data lake. There will be a transactional application which will house all user-facing applications. This will help the team with creating accurate recommendations or identifying the top customers for that particular store. The team will need to determine the correct approach with customers when bringing up the recommendations based on customer data and feedback. Based on different criteria like how many times a customer has received a recommendation, communication preferences, etc. they will know when and how to reach customers at the best time for higher engagement. The team will need to run a few pilots before the final project deadline in August, so they need to hire people who will ramp up to speed quickly and start contributing to the project right away. 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