Posted 6 days ago
Hybrid! ETL developer - Senior, 7 months contract
@ Dimensional Tech Inc.
Toronto, Ontario
Overview
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).
Responsibilities:
- 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
Requirements summary:
- 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
Tools & skills
Source and dates
Source type not verified · crelate
- Employer posting date
- 2026-11-04
- First seen by our source
- 2026-11-06
- Source record updated
- 2026-11-07
These dates describe the source record, not a live verification that the employer is still hiring. Check the original posting.
Job details
| Seniority | Senior |
| Department | Data & analytics |
| Work setting | Office |
| Position | Mostly sitting |
| Physical demands | physical low · computer high |
| Languages | English |
Summary and details written by AI from the posting; the employer’s posting is the authority.
Dimensional Tech Inc.
| Field | Value |
|---|---|
| Open jobs on Jobsy | 164 |
• 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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