Data Engineer

Description:

In a data-driven and AI-oriented environment, you will be responsible for the design, industrialization, and optimization of inter-application data pipelines. You will be involved in the entire data chain, from data ingestion to its use by data science teams and AI systems in production within a human-sized and multidisciplinary team. This role is within Process Intelligence (PI) team that combines functions such as Process Mining, Real Time Monitoring and Predictive AI

Key responsibilities:

• Design and maintain scalable data pipelines.
• Structure, transform, and optimize data in Snowflake.
• Implement multi-source ETL/ELT flows (ERP, APIs, files).
• Leverage the AWS environment, including S3, IAM, and various data services.
• Prepare data for Data Science teams and integrate AI/ML models into production.
• Ensure data quality, security, and governance.
• Provide input on data architecture.

Qualifications

• 5+ years of experience in data engineering, including significant experience in a cloud environment.
• Snowflake (MUST HAVE): Expertise in modeling, query optimization, cost management, and security.
• AWS: Strong knowledge of data and cloud services including S3, IAM, Glue, and Lambda.
• Languages: Advanced SQL and Python for data manipulation, automation, and ML integration.
• Data Engineering: Proven experience in ETL/ELT pipeline design.
• AI/ML Integration: Ability to prepare data for model training and deploy AI models into production workflows (batch or real-time).