Senior Data Engineer: Build Scalable AI Data Pipelines

Mistral AI SAS; Paris; Hybride; EUR 90 000 - 120 000; Plein temps

Avantages offerts par ce poste

Healthcare coverage

Parental leave

Relocation support

Retirement plans

Wellness programs

Meal allowance

Transportation allowances

Résumé du poste

Mistral AI SAS in Paris seeks a Senior Data Engineer to design, build and maintain scalable data infrastructure that powers state-of-the-art AI models and analytics for business teams.

You will work with large data volumes, implement robust ETL pipelines, ensure data quality, governance, and security, and collaborate with ML engineers to support model training and deployment workflows. The role demands 10+ years in data engineering and deep Python/SQL proficiency.

Qualifications

• 10+ years of experience in a Data Engineering role.
• Proficiency in Python and SQL.
• Experience with cloud platforms (e.g., AWS, GCP, Azure) and data warehousing solutions (e.g., Snowflake, BigQuery, Redshift, Clickhouse).
• Experience with dbt.

Responsabilités

• Design, build, and maintain scalable data pipelines, ETL processes, and analytics infrastructure.
• Collaborate with cross-functional teams to understand data needs and deliver high-quality, actionable solutions, e.g. work closely with machine learning teams to support model training, deployment pipelines, and feature stores.
• Optimize data storage, retrieval, processing, and queries for performance, scalability, and cost-efficiency.
• Define and enforce data governance, metadata management, and data lineage standards.
• Ensure data integrity, security, and compliance with industry standards.

Connaissances

Python

SQL

Cloud platforms

Data warehousing

dbt

Analytical skills

Outils

Software Engineering

Description du poste

Mistral AI SAS in Paris seeks a Senior Data Engineer to design, build and maintain scalable data infrastructure that powers state-of-the-art AI models and analytics for business teams.

You will work with large data volumes, implement robust ETL pipelines, ensure data quality, governance, and security, and collaborate with ML engineers to support model training and deployment workflows. The role demands 10+ years in data engineering and deep Python/SQL proficiency.