Publié il y a 7 jours
Hybrid! ETL developer - Senior, 7 months contract
@ Dimensional Tech Inc.
Toronto, Ontario
En bref
Dimensional Tech Inc. is hiring a senior ETL developer on a 7-month contract in Toronto, hybrid. The role builds production-grade data pipelines for AI/ML and Generative AI workloads on Azure. The posting states the hybrid arrangement and the contract duration (2026-11-23 to 2027-05-23).
Responsabilités :
- Design and develop scalable production-grade data pipelines for AI/ML and Generative AI
- Build ingestion, transformation and feature engineering workflows
- Prepare training, inference and RAG grounding datasets
- Integrate data pipelines with AI/ML solutions
Résumé des exigences :
- Significant hands-on experience with AI/ML and Generative AI data pipelines
- Advanced expertise in Python, SQL, ETL/ELT and APIs
- Working knowledge of Azure data and AI ecosystem
- Understanding of ML pipelines, training, inference and monitoring
Outils et compétences
Source et dates
Type de source non vérifié · crelate
- Date publiée par l’employeur
- 2026-11-04
- Première détection par notre source
- 2026-11-06
- Mise à jour du dossier source
- 2026-11-07
Ces dates décrivent le dossier source, pas une vérification en direct du recrutement. Consultez l’offre originale.
Détails du poste
| Niveau | Senior |
| Domaine | Données et analytique |
| Milieu de travail | Bureau |
| Position | Surtout assis |
| Exigences physiques | physique faible · ordinateur élevé |
| Langues | English |
Résumé et détails rédigés par l’IA à partir de l’offre; l’offre de l’employeur fait foi.
Dimensional Tech Inc.
| Champ | Valeur |
|---|---|
| Offres sur Jobsy | 172 |
• Location: Toronto, Ontario
• Duration: 2026-11-23 to 2027-05-23 ( 130 days)
• Job Type: Hybrid
• Openings: 1
Requirements:
• Significant hands-on experience designing and developing scalable, production-grade data pipelines for AI/ML and Generative AI workloads, including data ingestion, transformation, feature engineering, training and inference datasets, RAG/grounding data, and AI/ML pipeline integration.
• Advanced hands-on expertise in Python, SQL, ETL/ELT, APIs, data integration and transformation, and cloud-based data platforms, applying strong software engineering practices to build reliable, scalable, maintainable, and production-ready data solutions.
• Strong working knowledge of the Azure data and AI ecosystem, Azure Machine Learning, and Microsoft Foundry/Azure AI Foundry, with an understanding of ML pipelines, feature engineering, model training/testing, inference, monitoring, and the data requirements needed to support reliable enterprise AI/ML solutions.
Journal
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