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Senior Cloud Data Engineer
ProgiCanada
En tant que Senior Cloud Data Engineer chez Progi, vous serez responsable de la transformation et orchestration de la plateforme de données cloud , avec un focus particulier sur les couches Silver et
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Senior Software Engineer
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Senior Principal Engineer, Human Factors
CSL BehringSchwarzenburgThis role is a position in the Drug Delivery Systems & Packaging (DDSP) department within CSL Technical Operations. The ideal candidate has a solid track record in the development of drug delivery dev
Senior Principal Engineer, Human Factors
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Senior Principal Engineer, Human Factors
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Senior Principal Engineer, Human Factors
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Senior Principal Engineer, Human Factors
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Senior Principal Engineer, Human Factors
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Senior Principal Engineer, Human Factors
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Senior Principal Engineer, Human Factors
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Über
En tant que Senior Cloud Data Engineer chez Progi, vous serez responsable de la transformation et orchestration de la plateforme de données cloud , avec un focus particulier sur les couches Silver et Gold (BigQuery, Dataform, Cloud Composer) .
Votre rôle sera central dans l’évolution de notre plateforme vers un modèle data-driven avancé , incluant l’optimisation des coûts, la performance des pipelines et la mise en place des premières capacités en Machine Learning / AI en production .
Vous agirez en propriétaire end-to-end des pipelines de données (architecture medallion) et contribuerez activement à bâtir une plateforme robuste, performante et prête pour les usages analytiques et prédictifs.
Responsabilités principales
Ownership de la plateforme data (Medallion)
- Concevoir, construire et maintenir les couches Silver et Gold dans BigQuery
- Assurer l’implémentation complète d’une architecture Medallion (bronze / silver / gold)
- Garantir la qualité, la cohérence et la scalabilité des datasets
- Développer et maintenir des pipelines ELT/ETL avec Dataform et Cloud Composer
- Orchestrer les workflows de transformation et de chargement de données
- Assurer un monitoring fiable des pipelines en production
- Implémenter des stratégies d’ingestion via :
- APIs
- Bases de données (MySQL, etc.)
- Standardiser les flux d’ingestion pour assurer leur robustesse et leur réutilisabilité
- Optimiser les coûts et les performances des workloads BigQuery
- Mettre en place des bonnes pratiques :
- partitioning / clustering
- query optimization
- data lifecycle management
- Suivre et améliorer en continu l’efficacité de la plateforme
- Collaborer à la mise en place des premiers cas d’usage ML/AI
- Préparer les données pour des pipelines de machine learning en production
- Participer à l’intégration avec les outils GCP liés au ML (ex : Vertex AI)
- Contribuer à la mise en place et l’amélioration des pipelines CI/CD (Git, automatisation)
- Appliquer les standards d’ingénierie modernes (tests, versioning, documentation)
- Travailler étroitement avec les équipes BI, produit et techniques
- Participer à la définition des besoins analytiques et des modèles de données
- Promouvoir une culture de data engineering orientée performance et valeur métier
- Minimum 5 ans d’expérience en data engineering
- Minimum 2 ans sur Google Cloud Platform (GCP)
- Excellente maîtrise de :
- SQL (avancé)
- Python
- Expérience solide avec :
- BigQuery
- Dataform
- Cloud Composer
- Bonne compréhension des architectures :
- Data warehouse
- Medallion architecture
- Construction de pipelines de données en production
- Optimisation des coûts et performance BigQuery
- Migration ou modernisation vers le cloud
- Expérience avec des projets de Machine Learning (atout fort)
- Expérience avec CI/CD et Git
- Connaissance des outils d’ingestion (API, bases transactionnelles)
- Expérience dans un environnement data à forte volumétrie
- Ownership complet de la couche de transformation (pas juste builder)
- Impact direct sur :
- les coûts cloud
- la performance data
- la stratégie AI/ML
- Rôle hybride Data Engineer + Data Platform + AI en devenir
- Excellente maîtrise de :
- SQL (avancé)
- Python
- Expérience solide avec :
- BigQuery
- Dataform
- Cloud Composer
- Bonne compréhension des architectures :
- Data warehouse
- Medallion architecture
- Expérience pratique souhaitée
- Construction de pipelines de données en production
- Optimisation des coûts et performance BigQuery
- Migration ou modernisation vers le cloud
- Expérience avec des projets de Machine Learning (atout fort)
Sprachkenntnisse
- French
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