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En tant que Data Engineer, vous êtes l'architecte qui rend la donnée exploitable. Selon votre profil, vous interviendrez sur la construction de plateformes data robustes (Data Lakehouse) ou sur l'industrialisation de flux complexes destinés à l'IA.\nNos clients (Luxe, Retail, Télécom, Banque...) font face à une explosion des volumes et des sources de données. Votre rôle sera de garantir la fluidité, la qualité et la sécurité de ces flux.\nQuelques exemples de sujets du moment :\nMigration d'un legacy on-premise vers une architecture Cloud Lakehouse (Snowflake/Databricks). #CloudMigration\n\nIndustrialisation de pipelines complexes sur GCP (BigQuery, Dataform) avec une forte culture de l'observabilité (Dynatrace) et du CI/CD. #Orchestration\n\nDéploiement d'applications, d’API et de services IA (Algorithmes de prédictions ML, agents conversationnels, etc.) #MLOps\n\nAudit et refonte de pipelines d’ingestion pour réduire les coûts de calcul et de stockage sur GCP ou AWS. #Performance\n\nDéveloppement de composants Kafka, exposition via API et garantie de la performance des flux temps réel à l'échelle internationale. #Streaming\n\nRequirements\n\nL'humain :\nNous recherchons des talents :\nAyant un excellent relationnel pour faire le pont entre les besoins métiers et les contraintes IT,\n\nAvec la volonté de bâtir des infrastructures scalables et robustes,\n\nDotés d’un esprit d’analyse rigoureux,\n\nQui accordent une importance capitale à la qualité du code (CI/CD, tests unitaires) et à la documentation technique (Confluence/Jira),\n\nCurieux des nouvelles tendances (DataOps, IA générative appliquée au code),\n\nSensibles aux enjeux RSE pour intégrer des pratiques numériques durables,\n\nAvec l’envie de transmettre et d’apprendre au sein d’une communauté technique active,\n\nMaîtrisant l'anglais professionnel pour intervenir dans des contextes internationaux,\n\nDisposant de quatre années d'expérience minimum sur des sujets d'ingénierie de données.\n\nLes compétences techniques :\nVous êtes diplômé(e) d’une formation data à l’université ou en grande école et :\nMaîtrisez parfaitement Python et SQL (analytique et procédural),\n\nAvez une solide expérience sur un orchestrateur de workflow (Airflow, Prefect ou Dagster),\n\nConnaissez les outils de transformation moderne comme dbt (Data Build Tool),\n\nMaîtrisez au moins une 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