Closed listing
ML Engineer
- Mississauga, ON, Canada
Contract
This opening has closed.
The original listing is kept below for reference.
Job details
- Job type
- Contract
- Closing date
- Posting language
- English
- Posted
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Search current openingsOriginal job description
Archived listing. The details below describe a past opening.
We are looking for an ML engineer with expertise in Unity Catalog and Feature Store in Databricks to help us build and maintain a solid foundation for our data and machine learning workflows. You will work on organizing data, managing access, and enabling machine learning models to operate efficiently in production
What You Will Do -
What You Will Do -
- Set up and manage Unity Catalog in Databricks to organize and secure data access across teams
- Design and operationalize Feature Stores to support machine learning models in production
- Build efficient data pipelines to process and serve features to ML workflows
- Collaborate with teams using Databricks, Azure Cosmos DB, and other Azure tools to integrate data solutions
- Monitor and optimize the performance of pipelines and feature stores
- Strong experience with Unity Catalog in Databricks for managing data assets and access control
- Hands-on experience working with Databricks Feature Store or similar solutions
- Knowledge of building and maintaining scalable ETL pipelines in Databricks
- Familiarity with Azure tools like Azure Cosmos DB and ACR
- Understanding of machine learning workflows and how feature stores fit into the pipeline
- Strong problem-solving skills and a collaborative mindset
- Proficiency with Java
- Proficiency in Python and Spark for data engineering tasks
- Experience with monitoring tools like Splunk or Datadog to ensure system reliability
- Familiarity with AKS for deploying and managing containers
More about this job
Responsibilities
You will design and operationalize feature stores while managing Unity Catalog to secure data access across teams. Additionally, you will build efficient data pipelines and collaborate with cross-functional teams to integrate Azure-based data solutions.
Requirements
The role requires strong experience with Databricks Unity Catalog, Feature Store, and scalable ETL pipeline development. Proficiency in Python, Java, and Spark is essential, along with familiarity with Azure tools and container management via AKS.
Skills
- Unity Catalog
- Databricks
- Feature Store
- Python
- Java
- Spark
- Azure Cosmos DB
- ETL Pipelines
- Machine Learning
- Splunk
- Datadog
- AKS
- ACR
- Data Engineering
- Cloud Infrastructure
Visa sponsorship
Not detected in the job text
Categories
- Technology
- Software
- Data & Analytics
- Engineering
- Consulting
Keywords
- ML Engineer
- Unity Catalog
- Databricks
- Feature Store
- Azure
- Azure Cosmos DB
- ETL
- Python
- Java
- Spark
- Splunk
- Datadog
- AKS
- ACR
- Data Engineering
- Machine Learning
- Data Pipelines
- Cloud Computing
- Containerization
- System Reliability