Data Engineering Intern

Our mission and customers: We are creating the freedom for SMEs to succeed by delivering Europe's leading finance workspace with banking at its core, augmented by financial tools. We are proud to be rated 4.8 on Trustpilot based on 55,000+ reviews. Our culture puts customer satisfaction at the core of what we do, as proven by our Net Promoter Score of 75 (more about our culture ).

Our journey: Founded in 2017 by Alexandre and Steve , Qonto has grown to 1,700 Qontoers serving over 750,000 customers across 8 European countries. We have been profitable since 2023, and we are just getting started.

Our beliefs: We hire for skills and potential. With 80+ nationalities, 45% women, of which 56% of women in our leadership team, diversity isn't a program; It's who we are. We've built a discrimination-free hiring process because the best teams are built on merit.

AI at Qonto: AI is deeply embedded in how we work ()- Every Qontoer gets unlimited access to the best AI tools. We want people who experiment without waiting for permission, push AI beyond the obvious, know when to trust it, and when to question it.

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Join us as a Data Engineer Intern to help build the pipelines and tools that power Qonto's Data Platform . You'll ship a real, end-to-end project that makes data more accessible across the company, working alongside Charles , our Lead Data Engineer, and mentored day-to-day by Michael , Senior Data Engineer.

• Build data pipelines: Create and maintain batch and real-time pipelines that move data across Qonto's platform.
• Connect new data sources: Help ingest data from internal and external systems into our centralized warehouse.
• Build internal tools: Design web interfaces that make data more accessible to internal stakeholders.
• Automate and improve: Contribute to the tooling and automation that keeps the data platform reliable.
• Run your own project: Own an exploration project end-to-end and demo it to the team.

• Python: You write clean, maintainable code and know how to structure a real project, not just scripts.
• Data modeling: You understand how to structure data with tables, schemas, and SQL.
• Final-year student: You're in your final year (M2) of a Master's in Data Engineering, Data Science, or Software Engineering.
• AI-native: You use AI tools daily to learn faster and get more done.
• Communication: You communicate clearly and work smoothly with stakeholders across different teams.

• Daily mentorship: Hands-on, day-to-day mentorship from a senior Data Engineer on the team.
• Real ownership: You'll run your own exploration project end-to-end, not just support someone else's.
• Modern, AI-native stack: Unlimited access to AI tools like Claude Code to accelerate your work.