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Added 1 hour ago
Data Architect
Univeris
Toronto, ON
Full-time
Added 1 hour ago
Data Architect
Univeris
Toronto, ON
130,000 to 150,000 CAD / year
Full-time
Added 1 hour ago
Machine Learning Engineer
Experis Canada
Vancouver, BC
Contract
- Set up and manage Unity Catalog in Databricks to organize and secure data access across teams
Added 14 hours ago
Machine Learning Engineer - Early Career (Canada)
Jobright.ai
Canada
Full-time
…scalable infrastructure for AI agents, as well as optimize data processing and develop automated systems for model…
Added 14 hours ago
Machine Learning Engineer - Early Career (Canada)
Jobright.ai
Canada
Full-time
…scalable infrastructure for AI agents, as well as optimize data processing and develop automated systems for model…
Added 14 hours ago
Data Scientist, Early Career (Canada)
Jobright.ai
Canada
Full-time
…its innovative technologies. They are seeking an Early Career Data Scientist to develop predictive models, optimize AI performance, and analyze user data to enhance product…
Added 18 hours ago
Machine Learning Specialist
Querentia
Vancouver, BC
Contract
We are seeking an ML Dev Engineer with expertise in Databricks Unity Catalog and Feature Store to build and maintain scalable data and machine learning foundations. The role focuses on data…

Querentia

Machine Learning Specialist

Vancouver, BC, Canada

Contract

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At a glance

Automatically prepared from the listing. Check the original description for the full requirements.

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Responsibilities

The role involves setting up and managing Databricks Unity Catalog and designing operationalized Feature Stores for production ML models. You will also build efficient ETL pipelines and collaborate with teams to support and optimize machine learning workflows.

Requirements

Candidates must have strong hands-on experience with Databricks Unity Catalog, Feature Stores, and scalable ETL pipelines. Proficiency in Python, Spark, and Java, along with familiarity with Azure services and container management, is required.

Experience

5 to 10 years

Working hours

40 hours per week

Job type

Contract

Work arrangement

On-site

Skills

Databricks Unity Catalog
Feature Store
Python
Spark
Java
Azure Cosmos DB
Azure Container Registry
ETL Pipelines
Machine Learning
Splunk
Datadog
AKS
Data Engineering
Access Control
Data Organization

Visa sponsorship

Not detected in the job text

Keywords

Databricks
Unity Catalog
Feature Store
Machine Learning
ETL
Python
Spark
Java
Azure
Cosmos DB
ACR
Splunk
Datadog
AKS
Data Engineering
Data Pipelines
Access Control
Production ML
Container Deployment
IT Services

Original job description

We are seeking an ML Dev Engineer with expertise in Databricks Unity Catalog and Feature Store to build and maintain scalable data and machine learning foundations. The role focuses on data organization, access management, feature engineering, and supporting production ML workflows.

Key Responsibilities

Set up and manage Databricks Unity Catalog for data organization and secure access control.
Design and operationalize Feature Stores to support production ML models.
Build and maintain efficient data/ETL pipelines to process and serve ML features.
Integrate data solutions across Databricks, Azure Cosmos DB, ACR, and other Azure services.
Monitor, troubleshoot, and optimize pipeline and Feature Store performance.
Collaborate with data engineering and ML teams to support production workflows.

Required Skills & Experience

Strong hands-on experience with Databricks Unity Catalog, including data asset management and access control.
Experience with Databricks Feature Store or similar solutions.
Strong knowledge of scalable ETL pipelines in Databricks.
Proficiency in Python, Spark, and Java.
Familiarity with Azure Cosmos DB and Azure Container Registry (ACR).
Understanding of ML workflows and Feature Store architecture.
Experience with monitoring tools such as Splunk or Datadog.
Familiarity with AKS for container deployment and management.
Strong problem-solving and collaboration skills.

Apply by Oct 17, 2026

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