Data Platform Engineer Senior at Cafeyn

Paris, Ile-de-France, France -

Full Time

Start Date

Immediate

Expiry Date

21 Sep, 26

Salary

0.0

Posted On

23 Jun, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, AWS, Kubernetes, Airflow, Terraform, Snowflake, Data Modeling, CI/CD, Infrastructure as Code, Data Pipeline Design, API Development, GenAI, LLM, RAG Pipelines, Observability, Data Warehousing

Industry

technology;Information and Internet

Description

Join Cafeyn: Where Innovation Meets Inspiration Cafeyn is more than a platform— it is transforming the way people access and experience content. Since 2006, we’ve grown in a fast-evolving market, adapting to become a leading digital reading service with over 2 million users worldwide. Cafeyn gives readers unlimited, personalized access to thousands of newspapers and magazines, curated to fit their tastes and delivered seamlessly across devices. Our mission? 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. Infrastructure & Cloud Engineering 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. Data Warehousing & Modeling 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. Why Join Us 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. Our Tech stack: ☁️ 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 Requirements: You are/You have: 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. It’s nice if you have: Experience with the listed tools above, but having worked with similar technologies is fine Recruitment process: 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 Perks & benefits of working at Cafeyn Classic package 🎓 We provide a Swile card for your meal vouchers, Sidecare health insurance, and a mobility package to reimburse your transport subscription. Sports 🏃 We have a partnership with Wellpass that gives you access to fitness classes and wellness activities for both exercise and relaxation as you want. Mental Health 🧠 You have an access to our mental health platform teale, where you can book appointments with your psychologist or monitor your mental health. Hybrid policy 🏠 We allow you to work remotely two days per week. Cafeyn’s access 🗞️ We provide you with a VIP code for Cafeyn, giving you unlimited access to all content on our platform. Team life 🪅 We organize four office meet-ups per year. These occasions allow us to gather with our international offices, celebrate company updates, and spend quality time together. 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.

Responsibilities

Design and operate a robust data platform to power product features like recommendations and search. Build real-time data processors, batch pipelines, and scalable cloud infrastructure to enhance user experiences.