📈 BI Engineer (M/F)

The Business Intelligence Engineer (increasingly referred to as an Analytics Engineer) builds the pipeline that transforms raw data into reliable metrics: data modeling in the data warehouse, data transformations, the semantic layer, and dashboards for business teams.

🎯 Tasks

• Model decision-making data in the data warehouse (layered models, tests).
• Develop and document the transformations (dbt) and the semantic layer.
• Build reliable, high-performance dashboards for business units.
• Ensure a single definition of KPIs across the entire company.
• Train teams in self-service analytics and governance.

🛠️ Skills & Tech Stack 2026

• SQL expert and dimensional modeling.
• dbt: The standard for analytical transformation.
• Data warehouses: Snowflake, BigQuery, Databricks.
• BI: Power BI, Looker, Tableau, Metabase, Lightdash.
• Git, CI/CD, and engineering best practices applied to analytics.

⚠️ Legacy platforms (SAP BO, QlikView, on-premises OLAP cubes) are rapidly losing ground to the cloud.

💰 2026 Salaries (as reported in France)

• Junior: 40–47 k€
• Confirmed: 47–62 k€
• Senior / Lead: 62–80 k€
• Freelance: Average daily rate of 450–700 €.

🔍 Not to be confused with

The Data Analyst (who uses models to analyze data) and the Data Engineer (who ingests and routes raw data): the Analytics Engineer bridges the gap between the two.

❓ Frequently Asked Questions

Are BI and Analytics Engineering the same profession? Analytics Engineering is the modernization of the BI profession: the same objectives, but using the tools and practices of software engineering.

Power BI or Looker? Power BI dominates large French corporations, while Looker and Metabase dominate scale-ups; upfront modeling matters more than the visualization tool.

📈 Trends

Lead Analytics Engineer, Data Architect, Head of Data.