Software Development & Data Engineering Apprenticeship (January 2027 Cohort)

About the role

The AmaliTech Apprenticeship Programme, supported by DEG Impulse, offers a 6-month full-time (Monday to Friday) pathway for early-career talent and recent graduates to build or advance a career in software development and data engineering. Participants learn modern technologies through mentorship and project-based learning, with mentorship from senior engineers working with global clients.

Available tracks: Data Engineering, Python Backend + AI App Development, Java Backend Development, Quality Assurance (QA), JavaScript Full Stack and DevOps.

Required profile

• Based in Rwanda or willing to relocate.
• Final-year university student or recent graduate in Computer Science, IT, Engineering, Data Science or a related field.
• At least 6 months of practical programming experience (training, internship, projects, hackathons, online courses).
• Fluent English, spoken and written.
• Ability to work independently with minimal supervision and a growth-oriented mindset.

Required skills

• Data Engineering: basic SQL, introductory Python, data concepts; nice to have: data visualisation tools, ETL, cloud, PySpark, Microsoft Fabric.
• Python Backend: foundational Python, APIs, Git; nice to have: Flask/Django, AI/ML exposure.
• Java Backend: core Java, databases, Git; nice to have: IDEs, Spring Boot.
• QA: test cases, bug reports, Postman, Jira/Trello; nice to have: JMeter, Jenkins, CI/CD.
• JavaScript Full Stack: HTML5, CSS3, ES6+, React/Angular/Vue, Node.js/Express, Git; nice to have: testing, authentication, deployment platforms.
• DevOps: Linux command line, Git/GitHub; nice to have: cloud, CI/CD pipelines.

What we offer

• A stipend.
• A company laptop and meals (breakfast, lunch, snacks).
• Mentorship and structured guidance.
• Access to the latest tools and AI-driven technologies.
• Hands-on project exposure and a pathway to career opportunities within AmaliTech and its partners.

Applicants apply through the online application form, selecting their chosen specialisation.