Our mission? Creating the freedom for SMEs to succeed in business and beyond, by delivering Europe’s leading finance workspace. We combine business-class tools (seamless invoicing, spend management, and pre-accounting) with unwaveringly attentive 24/7 support, designed to help businesses breeze through all things finance.
Our journey: Founded by Alexandre and Steve in July 2017, Qonto has rapidly gained trust, serving over 600,000 customers. Thanks to our wonderful team of 1,600+ Qontoers, we also made it to the LinkedIn Top Companies French ranking!
Our values:
Customer focus | Prioritize customers in everything you do
Ownership | Own your part, get things done
Teamwork | Make (team)work easy
Mastery | Continuously raise the bar
Integrity | Always do what’s right, and respect people
Our beliefs: At Qonto, we're committed to fostering a welcoming environment where everyone can thrive. We prioritize evaluating applicants based solely on skills and potential, ensuring diversity with 55% international team members, 44% women, and 20% parents. Join us in building a workplace that celebrates diversity and individuality.
⭐ Mission Join us to build and maintain the scalable data platform that empowers our AI and Data teams to deliver value to over 600,000 customers. You will act as a technical bridge between our Data Platform and AI Product teams, ensuring our infrastructure allows us to ship advanced machine learning models and data projects efficiently.
👩💻🧑💻 As a Data Engineer at Qonto, you will
Run and evolve the Data Platform: You will own the set-up, management, and maintenance of our infrastructure tools (Airflow, Kubernetes, AWS), ensuring stability and scalability.
Bridge the gap with AI Products: You will collaborate closely with the AI team to implement tools that facilitate their work, helping operationalize machine learning models.
Drive cross-team initiatives: You will autonomously lead projects that span across the Platform and AI teams, ensuring alignment and smooth delivery.
Ensure Engineering Excellence: You will review design decisions, enforce high code quality standards (mainly in Python), and contribute to the continuous improvement of our engineering practices.
🤔 What you can expect
A central role: You will sit at the intersection of Data Platform and AI, working in a mature environment where your contributions directly impact the speed and quality of our AI innovations.
Modern Tech Stack: We work with a state-of-the-art cloud-native stack including Python, Airflow, Kubernetes, AWS, and Snowflake.
High Autonomy: You will join a team of senior engineers where ownership is key; you will be trusted to manage important platform topics from day one.
Hyper-growth context: You will evolve in a team that has grown significantly, working on challenges related to scaling data infrastructure for a leading European fintech.
🤝 About your future manager You will report to Charles, who is transitioning from a Staff Engineer role to lead the Data Platform team. Charles brings deep technical expertise and a strong history with Qonto's data stack. As a manager, he values autonomy and acts as a facilitator, ensuring his team has the space to grow while providing the technical guidance needed to succeed. He fosters a collaborative culture where team members are encouraged to step up and own their topics.
🏅 About You
Experience: You have 4+ years of experience in Software or Data Engineering, with a strong focus on platform and infrastructure topics.
Technical Mastery: You are proficient in Python (Java is a plus) and have solid experience with SQL and Kubernetes in a cloud-native environment (AWS preferred).
Tooling Expertise: You have hands-on experience managing orchestration tools like Airflow and are comfortable with CI/CD and infrastructure-as-code principles.
Communication: You have strong communication skills and can act as a technical bridge, translating constraints and requirements between Platform and Product teams effectively.
Languages: You speak fluent English.
At Qonto we understand that true diversity isn't just about ticking boxes on a hiring checklist. Apply regardless of the boxes you tick! Who knows? You may have the missing piece of the puzzle we've been searching for all along.
