Data Engineer Expérimenté – Hybrid, MLOps & GenAI

SFEIR Lille; Lille; Hybride; EUR 43 200 - 52 800; Plein temps

Résumé du poste

SFEIR Lille is seeking a data engineer to architect scalable data pipelines in Python, SQL, dbt and Airflow, and to manage data across BigQuery, Snowflake, Databricks and MLOps tools.

The role focuses on data quality, governance, orchestration and cost optimisation, transforming raw data into business insights and supporting AI‑driven workflows.

Based in Lille with a hybrid setup (2–3 remote days), the position offers growth through SFEIR Institute and hands‑on GenAI platforms.

Qualifications

• Architect data pipelines with Python, SQL, dbt and Airflow.
• Handle data across BigQuery, Snowflake, Databricks and MLOps tools.
• Ensure data quality, governance, orchestration and cost optimisation.
• Transform raw data into business insights.
• Experiment with generative AI to improve data workflows.

Responsabilités

• Architect data pipelines in Python, SQL, dbt and Airflow
• Manage data across BigQuery, Snowflake, Databricks and MLOps tools
• Ensure data quality, governance, orchestration and cost optimisation
• Transform raw data into business insights
• Experiment with generative AI to improve data workflows

Connaissances

Python

SQL

dbt

Airflow

BigQuery

Snowflake

Databricks

MLOps

Generative AI

Outils

Google Cloud

Azure

MLOps tools

Description du poste

SFEIR Lille is seeking a data engineer to architect scalable data pipelines in Python, SQL, dbt and Airflow, and to manage data across BigQuery, Snowflake, Databricks and MLOps tools.

The role focuses on data quality, governance, orchestration and cost optimisation, transforming raw data into business insights and supporting AI‑driven workflows.

Based in Lille with a hybrid setup (2–3 remote days), the position offers growth through SFEIR Institute and hands‑on GenAI platforms.