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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Platform Engineer Senior - Cafeyn H/F - **Company:** Cafeyn Group - **Location:** Paris, France (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Query Performance, Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Amazon Web Services, Cloud Engineering, Data as a Services, Information Engineering, Data Infrastructure, Data Systems, Data Warehousing, Python (Programming Language), Recommender Systems, Data Logging, Large Language Models, Snowflake, Backend, Core Data, Kubernetes, Real Time Data, Front End Software Development, Terraform, Programming Languages - **Published:** June 24, 2026 - **Apply:** https://www.hellowork.com/fr-fr/emplois/80556159.html ## About the Role 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., 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. 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 Experience with the listed tools above, but having worked with similar technologies is fine, bachelor degree EducationalOccupationalCredential associate degree ## Description 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, 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. - 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. 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. 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. 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. 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 AWS as cloud provider Python as main programming language Kubernetes (via EKS, the AWS-managed version) ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team) - [Inside Bitpanda's Tech Stack: Scaling a European Fintech Leader - Markus Dorner](https://www.wearedevelopers.com/videos/1979-inside-bitpanda-s-tech-stack-scaling-a-european-fintech-leader-markus-dorner) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [Nest.js - TypeScript in the backend can also be clean](https://www.wearedevelopers.com/videos/1033-nest-js-typescript-in-the-backend-can-also-be-clean) ## Related Articles - [Best Companies to Work For in Paris: Top 25 Companies in 2023 ](https://www.wearedevelopers.com/magazine/190-best-companies-to-work-for-in-paris-top-25-companies-in-2023) - [Best Companies to Work For in France: Top 25 Companies in 2023 ](https://www.wearedevelopers.com/magazine/189-best-companies-to-work-for-in-france-top-25-companies-in-2023) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Find a Developer Job: 12 Best Job Sites For Developers](https://www.wearedevelopers.com/magazine/165-find-a-developer-job-12-best-job-sites-for-developers) - [How Much FAANG Companies Actually Pay Software Engineers in 2025](https://www.wearedevelopers.com/magazine/230-how-much-faang-companies-actually-pay-software-engineers-in-2025) - [Where To Find Software Engineering Jobs](https://www.wearedevelopers.com/magazine/396-where-to-find-software-engineering-jobs)