Data Platform Engineer Senior Ajouter aux favoris
To empower individuals with access to trusted, high-quality content that fosters personal growth and discovery. Whether it's through the comprehensive collection of news and features on Cafeyn, the digital publishing solutions of Milibris, the fun and educative content for children on Kidjo, or the collections for manga lovers by Mangas.io, Cafeyn stands at the forefront of digital content experiences. Mission As a Senior Data Platform 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. Key Responsibilities Data APIs & Product-Facing Services
- 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).
- Design and maintain data pipelines with strong observability and reliability standards.
- 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.
- Work on core data infrastructure with direct impact on products and business outcomes.
- Hands-on exposure to GenAI and LLM systems in production, not just prototypes.
- High technical standards and a culture of ownership and accountability.
- Steep learning curve and clear path toward senior data engineering responsibilities.
- A scale-up environment combining autonomy, technical depth, and real impact.
- AWS as cloud provider
- Python as main programming language
- ☸ Kubernetes (via EKS, the AWS-managed version)
- Airflow for job orchestration
- Terraform to manage infrastructure
- Snowflake as datawarehouse
- 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.
- Experience with the listed tools above, but having worked with similar technologies is fine
- 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
- Classic package
- Sports
- Mental Health
- Hybrid policy
- Cafeyn's access
- Team life
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