Senior Analytics Engineer Data & AI

Role Overview

The Analytics Engineer is a true pivot between the Data Engineering teams, business, and data analysts. He transforms data into reliable, governed, and exploitable analytical assets. You rely on modern data transformation technologies (DBT) and visualization (Power BI), as well as the capabilities offered by AI generation, to accelerate the creation of value and democratize access to data within organizations.

What You Will Do

Within project teams, you will be responsible for the following missions: Gathering, analyzing, and challenging business needs to design analytical solutions responding to steering and decision-making issues; Designing, developing, and industrializing data transformation flows with DBT on modern data platforms (Databricks, Snowflake, GCP BigQuery, Microsoft Fabric); Building and maintaining robust analytical data models (datamarts, semantic layer, business metrics, dimensions, and facts) ensuring coherence and reusability.

Why It Might Be a Fit

As a Senior Data Engineer, you justify successful experiences on high-stakes data & analytics projects, combining data transformation and decision-making restitution. You have a confirmed mastery of DBT, Python, and strong expertise in SQL and analytical modeling principles.

Requirements

• Bachelor’s degree or equivalent
• Minimum 7 years of experience in data engineering, with significant experience combining data visualization and data transformation (analytics engineering)
• Confirmed mastery of DBT, Python
• Strong expertise in SQL and mastery of analytical modeling principles (Data Warehouse, Data Marts, Dimensional Approach, Business Metrics, Semantic Layer)
• Knowledge of Analytics Engineering industrialization practices: Git, CI/CD, Observability, Data Quality, Automated Tests, and Deployments
• Sensitivity to Data Product approaches and the governance of analytical assets
• Excellent mastery of Power BI: Tabular Modeling, DAX, Power Query, Performance Optimization, and Analytical Experience Design
• Ability to transform complex problems into actionable, understandable, and adopted indicators
• Good understanding of self-service analytics concepts, data governance, and decision-making adoption
• Knowledge of Tableau, Qlik, or Looker is a plus
• Mastery of AI generation as a productivity accelerator in Analytics Engineering and BI activities: SQL code, DBT, and DAX generation and review, Automated documentation creation, Assisted quality test creation, Exploratory analysis acceleration, Specification and business insight generation
• Good understanding of architectures in Medallion, Lakehouse, Data Warehouse Cloud, and Modern Data Platform
• Experience in Azure, AWS, or GCP, Snowflake, Microsoft Fabric, or Google BigQuery environments
• Mastery of DevOps practices applied to data: versioning, continuous integration, automated deployments, and monitoring
• Experience in Agile environments (Scrum, Safe, Kanban, Product Team)
• Mastery of collaborative and management tools (Jira, Azure DevOps, Confluence, GitHub)
• Ease in collaboration with pluridisciplinary teams
• Good professional English level in an international context (B2 minimum)
• Microsoft Fabric Analytics Engineer Associate (DP-600)
• Microsoft Power BI Data Analyst (PL-300)
• DBT Analytics Engineer Certification

Benefits

• Training plan to accompany your career (editor training, certifications) through our partnerships, and proximity management by experts
• Modern city-center offices
• Top 5 of the Great Place to Work Palmarès
• Telecommuting up to 5 days according to missions, 100€ equipment bonus
• Mobility in France and abroad
• Top 1% of companies evaluated by Ecovadis in the social, environmental, and ethical domain
• Restaurant tickets, vacation premium, 50% transport (public transport subscription), mutual
• Permanent disability (dedicated consultant for employees with disabilities and their caregivers)
• Employee shareholding
• Recruitment premium
• RTT