Key skills
AWSAzureCloudDockerETLGoogle Cloud PlatformSparkSQLELTData EngineeringDatabricksGCPGoogle CloudGitVersion ControlCI/CDRemote Work
About this role
Role Overview
- Design and deploy high-performance data pipelines on Databricks
- Manage data ingestion through to making data available to business teams
- Model and structure data
- Ensure data quality, availability, and optimal usability
- Optimize ETL/ELT processes and the performance of Spark workflows
- Collaborate closely with Data Scientists, Product Owners, and business teams
- Understand their needs and deliver relevant solutions
- Contribute to the continuous improvement of best practices in Data Engineering, Cloud, and CI/CD
Requirements
- Engineering degree
- At least 3 years of experience in Data Engineering
- Proven hands-on experience with Databricks or Spark
- Proficiency with Cloud environments (Azure, AWS, or GCP)
- Version control (Git)
- DevOps practices (CI/CD, Docker)
- Strong SQL skills
- Data modeling
- Team player
- Technical curiosity
- Desire to work on innovative projects
Tech Stack
- AWS
- Azure
- Cloud
- Docker
- ETL
- Google Cloud Platform
- Spark
- SQL
Benefits
- Remote work (up to 70%)
- Professional equality policy
- Parental benefits
- Work-life balance
- Sustainable mobility
- Technical certifications and on-demand training
- Personalized support with your career manager
- 9-month onboarding program
- Employee share ownership plan
- PERCOL
- Attractive employee benefits with discounted rates (travel, concerts, cinema tickets...)
- Partial holiday reimbursement
- Reimbursement of your sports or cultural membership
- Personal development (driving license training, pastry classes, nutrition...)