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Confirmed on the employer's own hiring board on Nov 12, 2026. First seen by Alion on Jul 27, 2026. Querentia scores C on the Alion truth index.

Overview
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Querentia is a recruitment and talent solutions firm headquartered in Toronto that places technology and non-technology professionals with client organisations across North America. Established in 2021 as Querentia Inc., the firm also lists offices in New York, San Jose and Dover, Delaware, and fills contract and permanent roles for clients in Toronto, Montreal, Vancouver, Ottawa and Calgary. Its open assignments are mostly IT contracts such as SAP and Workday consultants, Databricks and GCP data engineers, Salesforce consultants, enterprise and solution architects, computer vision and AI engineers, program managers and digital marketing specialists.
Role: Senior ML Engineer - Lead

Job Summary

We are seeking a Senior ML Engineer - Lead to design, build, and optimize scalable data and machine learning solutions on Azure. The ideal candidate will have strong expertise in Azure Data Factory, Azure Databricks, Azure Machine Learning, PySpark, SQL, and Python , along with proven leadership experience managing technical teams.

Key Responsibilities

Design, develop, and maintain scalable data pipelines using Azure Data Factory (ADF) .

Build ETL/ELT solutions using Azure Databricks and PySpark .

Develop and optimize data architectures to support machine learning and analytics.

Build infrastructure for data extraction, transformation, and loading using Azure big data technologies.

Collaborate with Product, Data Science, Design, and business stakeholders to deliver data-driven solutions.

Develop data tools and platforms to support analytics and machine learning initiatives.

Ensure performance, scalability, security, and reliability of Azure data solutions.

Lead and mentor a team of 10-15 engineers while driving technical delivery.

Required Skills & Experience

Strong hands-on experience with:

Azure Data Factory (ADF)

Azure Databricks

Azure Machine Learning

PySpark

Python

SQL

Experience with Azure Security , DevOps , and cloud-based data platforms.

Exposure to AWS is an asset.

Strong understanding of Spark and modern data engineering practices.

Excellent leadership, presentation, stakeholder management, and communication skills.

Proven experience leading high-performing engineering teams.

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