Staff Data Engineer

Overview 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 preaccounting with unwaveringly attentive 24/7 support designed to help businesses breeze through all things finance. Our journey: Founded by and 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 French ranking. Our values: Customer focus | Prioritize customers in everything you do; Ownership | Own your part, get things done; Teamwork | Make teamwork 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. Role Mission: As a Staff Data Engineer your mission is to architect and implement scalable data platform tools that support AI product development, enabling our teams to deploy and operate AI models effectively. You will act as the technical bridge between AI Product teams and Platform Engineering, playing a central role in Qonto’s strategy to integrate AI across business areas and improve customer experience for our 400,000 clients. As a Staff Data Engineer at Qonto you will: Bridge & Translate: Act as the technical bridge between ML product teams and platform engineering, translating ML requirements into scalable platform features. Design Architecture: Lead the design of cross-functional data architecture ensuring consistency, scalability, and reliability across reporting, analytics and ML use cases. Establish Standards: Partner with engineering leadership to establish platform standards, governance frameworks, and best practices. Optimize Infrastructure: Manage and maintain the data platform Snowflake orchestration with a focus on reliability, performance and cost. Drive Quality: Ensure platform documentation is up-to-date and establish robust data quality KPIs and monitoring within your first 9 months. What you can expect Strategic Context: You will join a rapidly growing environment where AI is becoming increasingly strategic, requiring robust infrastructure in a regulated financial context. Methodologies: We balance short-term delivery for AI product teams with long-term platform evolution, designing tools almost from scratch. Team: You will work in a team of experienced Senior and Staff engineers with high autonomy, influencing a tech organization of 500 engineers. Tools: We work with Python, Java, Kubernetes, Snowflake and modern ML platform tools (e.g., MLflow, Kubeflow, SageMaker). Impact: You will directly contribute to raising the overall AI maturity of Qonto, enabling us to serve our customers better through intelligent automation. About your future manager Your Future Manager will be Lead of the Data Platform team. His background? Charles is transitioning from an Individual Contributor role into a leadership position after building strong expertise in data platform topics and architecture. What does he bring to the team? Charles has a hands-on architect, embedded leadership style: he stays close to the technical reality, helps unblock complex topics, and supports the team in making pragmatic architectural decisions. He values humility, collaboration and clear communication and fosters an environment where autonomy is encouraged and supported through impactful projects. About You Experience: 8 years of experience in data engineering with demonstrated progression toward architectural roles, including deep expertise in designing and scaling data platforms. ML Lifecycle Mastery: Strong understanding of the full ML lifecycle: experimentation, training, deployment, monitoring and retraining, with experience using modern ML platforms and tools (MLflow, Kubeflow, SageMaker, TensorBoard or similar). Architectural Thinking: Proven ability to bridge technical and product perspectives, translating business needs into technical solutions with a track record of making complex tradeoffs and driving technical consensus. Technical Leadership: Track record of influencing technical direction and mentoring engineering teams with excellent communication skills to articulate technical vision to diverse stakeholders. Regulated Environment: Experience working in regulated environments; financial services preferred and a strong mindset for governance and compliance. Perks A tailormade and dynamic career track An inclusive work environment Offices in Paris, Berlin, Milan, Barcelona and Belgrade Competitive salary package; Meal vouchers; Public transportation reimbursement A great health insurance depending on the country Employee wellbeing initiatives: access to mental health support and wellness offers Disability support and parental benefits with selected partners Monthly team events #J-18808-Ljbffr