Senior Data engineer, Cafeyn

• Significant experience with Python (5+ years of professional experience with it)
• Experience in architecting and deploying data systems on AWS, GCP or similar
• Have experience dealing with container orchestration, preferably with Kubernetes
• Fluent in English
• Driven by a global tech vision and concern for optimizing solutions, technically, functionally and financially
• Ability to collaborate with different stakeholders and teams
• You don’t have to match all the requirements, if you feel this offer could be a great opportunity for you, reach out anyways! We hire based on talent and we promote inclusivity inside Cafeyn and strongly believe that our culture is strongest when it is the most diverse

Desirable

• As a Senior Data Engineer at Cafeyn, you will play a key role in designing, building, and operating a robust data platform that powers core product features such as content recommendations, search, and dynamic page skeletons
• You will work at the intersection of product, backend engineering, data science, and infrastructure to deliver scalable, reliable, and high-performance data systems that directly impact millions of users
• Your mission is to turn data into real-time, production-grade services that power personalized and intelligent user experiences
• You will be a part of the Data Engineering team (3 people for now), which depends on the Cafeyn tech team. Their mission is also to support other data specialists (15 people in total distributed in several teams like product and finance)
• Design, develop, and maintain Python-based data services powering critical product features (content recommendations, search systems, page skeleton generation)
• Build and operate real-time data processors as well as robust batch pipelines supporting both analytical and operational use cases
• Collaborate closely with backend and frontend teams to integrate data services seamlessly into user journeys
• Contribute to architecture decisions that improve scalability and maintainability of our systems
• Contribute to the industrialization and scalability of AI-powered features (e.g., RAG pipelines, model serving, evaluation workflows)
• Contribute to the architecture and evolution of our cloud-based data infrastructure
• Implement infrastructure-as-code through IaC and CI/CD pipelines to ensure reliable deployments and reproducibility
• Strengthen observability, logging, and monitoring across data services and pipelines
• Design and evolve scalable data warehouse models to support analytics, experimentation, and product-facing APIs
• Optimize storage, query performance, and cost efficiency in our datawarehouse
• Establish best practices for data modeling, governance, documentation, and ownership
• Those are great opportunities to get hands-on experience with a modern data and tech platform, with a high level of autonomy and impact on a customer-facing product

• First interview with our Talent acquisition manager Léa
• Informal meeting with Raphaël, Data engineering manager
• Technical assignment to perform live in our Paris office with Raphaël & Thomas, Data engineer
• Culture fit with our data team members
• Last interview with Thomas, CTO & Vincent, Director of Engineering