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Salary
≈ $47k – $74k per year (Estimated)
Location
Hybrid (France)
Seniority
Senior
Employment
Freelance

First seen by Alion on Oct 19, 2026.

Overview
Company
Impact
Profile match
Craftman Data is a French consultancy specialised in data, artificial intelligence and digital transformation. Its consultants are placed on client projects as data engineers, data scientists and technical leads working with GCP, Java, Python and Spark. The company is headquartered in Paris, France.
Contexte & Enjeux

Rattaché(e) au Responsable Pilotage de la Performance, vous intervenez directement auprès de la Direction COMEX Marchandise pour éclairer la dynamique des Parts de Marché (PDM) de Carrefour.

La mission couvre l'ensemble du spectre d'analyse, du suivi hebdomadaire jusqu'aux projections et visions pluriannuelles.

Missions & Livrables

En forte autonomie, vous accompagnez la Direction dans la compréhension fine et le pilotage des Parts de Marché :

  • Reportings & Projections : Réalisation des reportings hebdomadaires et projections pluriannuelles de PDM pour le COMEX Marchandise (Google Slides).

  • Data Visualisation : Création et optimisation de dashboards interactifs d'aide à la décision (Looker Studio, Tableau, Google Sheets).

  • Études Ad Hoc : Notes d'analyses ciblées éclairant les impacts business sur la PDM.

  • Data Processing : Rédaction et optimisation de scripts d'extraction et de modélisation de données (SQL / BigQuery, Python).

Profil recherché

Séniorité : > 7 ans d'expérience en Data Analyse (Bac+5 École d'ingénieur ou Université).

Secteur : Expérience significative dans le Retail / Grande Distribution appréciée.

Must Have :

  • SQL & BigQuery : Maîtrise avancée, rédaction et optimisation de requêtes complexes sur gros volumes.

  • Dataviz / Looker Studio : Création et optimisation de dashboards interactifs et suivi des KPIs critiques métiers.

  • Aisance analytique & Communication : Capacité à restituer des analyses claires auprès de profils COMEX / Direction.

Nice to Have :

  • Modélisation de pipelines de données sous BigQuery.

  • Python analytique (Pandas, NumPy, PySpark).

  • Environnement Cloud GCP / Azure, Git / GitLab CI, pratiques Agile (Scrum).

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