Data Engineer expérimenté(e)

About Our Client

Our client is a fast-growing technology player, specializing in the development of innovative SaaS solutions for businesses. Driven by a product culture and strong technological ambition, the company invests heavily in data architectures and artificial intelligence systems to design a new generation of intelligent and automated tools.

The work environment is characterized by:

• High technical standards
• Structuring projects with high impact
• A culture of autonomy and accountability
• Close collaboration between Product, Data, and AI teams

Role Overview

To strengthen its technical teams, our client is recruiting an experienced Data Engineer. Reporting to the Data & AI team, you will be involved in the design, development, and operation of data infrastructures at the core of the platform's future intelligent services. Your role will be key in structuring data flows and architectures that feed advanced AI systems in production.

Responsibilities

• Design and maintain robust and scalable data pipelines
• Develop data workflows on Databricks
• Structure and exploit complex data in cloud environments
• Participate in exposing services via APIs
• Ensure data quality, security, and reliability
• Collaborate closely with AI, Product, and Engineering teams
• Participate in the continuous improvement of the platform's architectures and performance

You will work in a modern, production-oriented technical environment with a strong DevOps culture and a focus on industrializing data solutions.

Profile

• Higher education in computer science or data engineering
• At least 5 years of confirmed experience in production data environments
• Excellent command of Python, SQL, Spark, Azure, and Databricks
• Comfortable with FastAPI, Docker, Kubernetes, Git, CI/CD pipelines, and modern cloud architectures
• Experience in end-to-end intervention, from design to deployment
• Experience with knowledge graphs, RAG architectures, vector databases, or multi-tenant SaaS environments is a significant asset
• Autonomous, structured, and quality-oriented
• Enjoy collaborating with multidisciplinary teams and contributing to innovative, high-value-added projects