Full Stack Software Engineer

Datascience

Responsibilities:

• Collaborate with the software development team to maintain software SAS based applications, as well as develop and maintain high-quality software applications using Angular and Java Spring Boot programming languages.
• Work with stakeholders to gather and clarify software requirements and contribute to the design and architecture of software solutions.
• Participate in code reviews to ensure code quality, maintainability, and adherence to best practices.
• Maintain comprehensive documentation for software projects, including technical specifications, user guides, and release notes.
• Collaborate with cross-functional teams, including product managers, designers, and quality assurance engineers, to deliver software projects on time and within scope.
• Identify and address technical challenges, troubleshoot issues, and propose innovative solutions.

Requirements:

• - Bachelor s degree in Computer Science, Software Engineering, or a related field (or equivalent hands-on experience).
• - Strong proficiency in Java and Spring Boot.
• - Solid experience with Angular (v12+) for front-end development.
• - Strong understanding of REST API design principles.
• - Hands-on experience with PostgreSQL or similar relational databases.
• - Experience with version control systems such as Git.
• - Familiarity with Agile/Scrum methodologies, including working in sprints, stand-ups, and iterative delivery.
• - Understanding of full-stack integration.
• - Basic knowledge of containerization and deployment (e.g., Docker) and CI/CD pipelines is a plus.
• - Awareness of web security best practices.
• - Experience with testing practices.
• - Strong problem-solving skills with the ability to debug across the full stack (frontend, backend, database).
• - Excellent communication and collaboration skills, with the ability to work effectively in cross-functional teams.
• - Self-driven mindset with a willingness to learn new tools, frameworks, and technologies.

Preferred Qualifications:

• Experience with containerization technologies like Docker and Kubernetes.
• Familiarity with cloud platforms such as AWS, Azure, or Google Cloud.
• Knowledge of message queueing systems like Kafka or ActiveMQ.