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- Salary
- —
- Openings
- 1
- Posted
- 3 days ago
- Work mode
- In office
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Job description
Role Overview
We are looking for a proficient Full Stack Developer with extensive hands-on expertise in Java 17/21, Spring Boot, Microservices, AWS, and Databricks. The ideal candidate must demonstrate a strong foundation in Java fundamentals and have broad experience across all phases of the software development lifecycle (SDLC). Additionally, familiarity with AI-assisted coding tools to enhance productivity and maintain code quality is essential.
Primary Duties
- Architect, implement, test, and deploy scalable enterprise-grade applications utilizing Java 17 and 21.
- Develop and sustain RESTful APIs and Microservices employing Spring Boot framework.
- Produce clean, maintainable, and high-performing code aligned with industry best practices.
- Engage in initiatives focused on application modernization and cloud migration readiness.
- Leverage AI-enabled development tools like GitHub Copilot and Claude to boost development efficiency and code quality.
- Work in coordination with business analysts, solution architects, quality assurance, and DevOps teams through all SDLC stages.
- Diagnose and resolve issues in production environments promptly.
- Contribute actively to code reviews and participate in continual improvement efforts.
Technical Skills Required
- Deep understanding of core Java concepts including Collections Framework, multithreading and concurrency management.
- Proficiency with Streams, Lambda expressions, memory management, JVM internals, and exception handling.
- Expertise in using design patterns and performance tuning techniques.
- Practical experience implementing Java 17 and/or Java 21 codebases.
- Strong command of Spring Boot, Spring MVC, and Spring Data JPA.
- Hands-on experience in Microservices architecture and REST API design.
- Proficiency with Apache Kafka and event-driven system architectures.
- Experience with AI-assisted software development tools to accelerate coding processes.
- Knowledge of Databricks workflows for data processing.
- Familiarity with AWS cloud offerings such as EC2, S3, RDS, Lambda, IAM, and CloudWatch.
Additional Knowledge
- Basic understanding of Python and Pyspark languages.
- Working knowledge of SQL and PL/SQL query languages.
- Familiarity with version control using Git, continuous integration and delivery pipelines, Maven/Gradle build tools, and Agile project management methodologies.