Data Engineer

About Us

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.

As part of strengthening its technical teams, our client is recruiting an experienced Data Engineer.

Mission

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 the 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 drive for industrializing data solutions.

Profile

With a higher education in computer science or data engineering, you have at least 5 years of confirmed experience in production data environments.

You have excellent command of the following environments:

• Python
• SQL
• Spark
• Azure
• Databricks

You are also comfortable with:

• FastAPI
• Docker
• Kubernetes
• Git
• CI/CD pipelines
• Modern cloud architectures

You appreciate demanding technical environments and are capable of intervening on end-to-end topics, from design to deployment.

Experience with knowledge graphs, RAG architectures, vector databases, or multi-tenant SaaS environments will be a real asset.

Autonomous, structured, and quality-oriented, you enjoy collaborating with multidisciplinary teams and contributing to innovative projects with high added value.