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Kami logo

Data Engineering Intern 26/27

Kami
Posted Jul 2, 2026, 12:03 PM UTC
🇳🇿New Zealand🏢Hybrid📁Data & Analytics
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About Kami Kami is a thriving organisation filled to the brim with talented, creative, and passionate people! It’s hard not to love what you do when our leading digital classroom platform offers meaningful solutions to over 70 million users worldwide, empowering students and supporting teachers! You’ll be joining at a pretty magical time. Kami’s user base is growing by the day. With over 170 team members across the world, we couldn’t be prouder of the accomplishments and milestones we’ve achieved to date. Now, this is your chance to join our team and become an integral member of Kami’s growth, while shaping your own future (and having fun doing it)! The Opportunity We're looking for individuals from any stage of their student journey - in your final year, about to get your 3rd graduate degree, or graduated within the last 12 months - all are welcome. We are passionate about doing meaningful work with future leaders, builders and change makers. You’ll be analysing and interpreting millions of data points, to connect the dots and help inform data-driven decision making in our product builds. You’ll be embedded into our Engineering teams, working alongside Data Engineers, Data Analysts, Software Engineers, and more. Join our summer Data Engineer Internship at Kami HQ! We are hiring for potential and we’re most interested in what makes you, you . So let your CV, your interviews, and every step in between reflect your authentic experiences and unique perspective. This summer there is 1 Data Engineering Internship and they will be hired on a rolling basis . The internship is full-time (40 hours a week), hybrid in our Auckland office, and paid . The internship runs from November 9 2026 to February 12 2027 (we can be flexible depending on your last exam). We encourage you to apply early - offers may be made before the closing date of August 31 2026. What You’ll Do Build and maintain data infrastructure Contribute to the development and maintenance of data pipelines, supporting infrastructure with guidance from experienced data engineers. Contribute to maintaining data warehouses, databases, and analytics infrastructure. Help ensure data is reliable, accurate, and available for reporting and analytics. Write clean, maintainable code and follow data engineering best practices. Learn modern data engineering tools, technologies, and best practices. Build practical experience delivering real-world data solutions while growing your technical and professional skills. Continuously improve data quality Help investigate data issues and troubleshoot pipeline failures. Support efforts to improve data quality, performance, and reliability through testing and monitoring. Contribute to documenting processes and improving operational workflows. Collaborate with cross-functional teams Partner with Product Managers, Software Engineers, Data Analysts and other Data Engineer team members to understand data requirements and support business needs. Participate in team planning, knowledge sharing, and technical reviews while building strong cross-functional relationships. Communicate progress, ask questions, and seek feedback throughout the internship What You’ll Bring The logistics Full-time working rights in New Zealand Availability to commit full-time between November – February Studying a relevant degree including Computer Science, Software Engineering, Data and AI, or a similar field We’re looking for potential rather than experience, so we're focusing on Curious, capable problem-solving - how you think, learn, and approach challenges matters more to us than what you already know. High coachability and growth mindset - you positively receive feedback, embrace new ideas and use it as an opportunity to learn and grow. Mission-driven and intentional - you are motivated by purpose, taking the time to understand the “why” so your work has meaningful impact. Great communication and collaboration skills - you share information and ask questions openly, listen actively, and foster productive collaboration.

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