> Markdown version of [/jobs/ext/4160246-back-end-developer](https://www.wearedevelopers.com/jobs/ext/4160246-back-end-developer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Back End Developer - **Company:** Amtex Systems Inc - **Location:** Dallas, TX, United States - **Contract:** Permanent contract - **Skills:** Clean Code Principles, Java (Programming Language), JavaScript (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Systems Engineering, HTML5, Microsoft Azure, Big Data, Cascading Style Sheets (CSS), Cloud Computing, Cloud Engineering, Databases, Continuous Integration, Data Integration, Relational Databases, DevOps, Django Web Framework, Memory Management, Java Platform Enterprise Edition (J2EE), Github, Spring Framework, Junit, Python (Programming Language), PostgreSQL, Machine Learning, Microsoft SQL Server, MongoDB, NoSQL, OpenShift, Oracle (Applications), Performance Tuning, RabbitMQ, Redis, Mockito, Software Deployment, SQL Databases, TypeScript, Web Applications, Web Application Frameworks, Data Processing, Scripting, Google Cloud, Cloud Platform System, Modern Ui, Spring Cloud, ReactJS, Flask (Web Framework), Delivery Pipeline, Spring-boot, Backend, Fastapi, Vue.js, Spring Data, Pytest, Containerization, AngularJS, Integration Tests, Solid Principles, Kubernetes, Infrastructure Automation Frameworks, Data Analytics, Apache Kafka, Front End Software Development, Restful APIs, Data Pipelines, Docker, Jenkins, Microservices - **Published:** October 8, 2026 - **Apply:** https://www.dice.com/job-detail/79c8334f-1707-4557-ba62-89d321f8c29c ## About the Role Core Java Ecosystem: Deep proficiency in Java (Java 11 / 17 / 21) and the Spring Framework (Spring Boot, Spring Cloud, Spring Data). Python Engineering: Strong experience with Python backend frameworks (FastAPI, Flask, or Django) and scripting for automation or data processing. Containerization & Orchestration: Advanced experience with Docker and production Kubernetes management (deployments, pods, services, ingress). Frontend Technologies: Solid knowledge of HTML5, CSS3, JavaScript/TypeScript, and modern UI frameworks like React, Angular, or Vue.js. Databases & Messaging: Competency in relational databases (Oracle, PostgreSQL, SQL Server) and NoSQL options (MongoDB, Redis) alongside messaging queues like Apache Kafka or RabbitMQ. Cloud Platforms: Hands-on experience deploying infrastructure on major cloud environments (AWS, Google Cloud Platform, or Azure). ## Description We are seeking a highly skilled Back End Developer with a powerful combination of enterprise Java systems engineering, Python backend/automation capability, and modern Kubernetes cloud-native orchestration. In this role, you will design, develop, deploy, and support secure, scalable data-driven web applications, microservices, and shared platform capabilities. You will work across the entire stack-from developing responsive user interfaces to managing robust backend logic, automated data pipelines, and infrastructure-as-code deployments., Development: Design, build, and maintain robust, scalable end-to-end applications using modern frontend frameworks and enterprise backend ecosystems. Backend & API Engineering: Build clean, secure RESTful APIs, asynchronous event-driven integrations, and microservices leveraging Java (Spring Boot) and Python frameworks. Cloud-Native Architecture: Containerize services using Docker and manage deployments onto orchestrators like Kubernetes or Red Hat Openshift Data Integration & Automation: Develop Python-based data pipelines for ingestion, transformation, automated reporting, or AI/ML model integrations. CI/CD & DevOps: Implement and optimize automated continuous integration and deployment pipelines (e.g., GitHub Actions, Jenkins). Code Quality & Testing: Write clean, modular, and maintainable code adhering to SOLID principles. Build comprehensive unit and integration test suites using JUnit, Mockito, and PyTest. Performance Tuning: Optimize application throughput, memory management, and SQL/NoSQL query execution for large datasets.