Java Full Stack QC Specialist

Job highlights

• 3-5 years of experience in Java Full Stack Development,technical training or comparable technical roles
• Experience with frontend frameworks such as React or Angular
• Hands-on experience with relational,NoSQL databases like MySQL,PostgreSQL,MongoDB,or Redis

The Java Full Stack Specialist evaluates learners technical proficiency in full-stack development, provides mentorship, and ensures alignment with industry standards. This role involves comprehensive assessment across Java, backend frameworks, frontend technologies, and database management, while providing actionable feedback to accelerate learner development. The specialist collaborates closely with trainers and cross-functional teams to uphold quality standards throughout the training lifecycle.

Responsibilities:

• Design and execute quality audit frameworks for professional training programs
• Conduct technical interviews to assess learners proficiency in Java, Spring Boot, React/Angular, and database technologies.
• Create assessments including quizzes and coding challenges to evaluate learners understanding of the concepts and ability to apply them.
• Review full-stack project submissions by the learners for functionality, performance, code quality, and overall design.
• Deliver clear, actionable feedback that identifies strengths and provides guidance for technical skill enhancement.
• Document assessment outcomes, interview insights, and performance trends systematically
• Collaborate with trainers to share insights on learner performance and work towards enhancing training outcomes.

Experience and Skills Required:

• 3-5 years of experience in Java Full Stack Development, technical training or comparable technical roles.
• Strong proficiency in Java, Spring Boot, RESTful APIs, and backend architecture.
• Experience with frontend frameworks such as React or Angular.
• Solid foundation in Data Structures, Algorithms, and SQL.
• Hands-on experience with relational, NoSQL databases like MySQL, PostgreSQL, MongoDB, or Redis.
• Familiarity with cloud platforms (AWS, Azure, or GCP) for deployment.
• Working knowledge of CI/CD pipelines, containerization (Docker/Kubernetes), and Git/GitHub workflows.
• Exposure to AI integrations or Generative AI APIs is an added advantage.
• Strong analytical thinking, attention to detail, communication, and coaching abilities.