Job Description
We're looking for an ML Engineer with strong Azure data engineering and machine learning experience to design, build, and maintain scalable data pipelines and infrastructure. The ideal candidate brings hands-on expertise across Azure Data Factory, Databricks, and PySpark, and is comfortable working with cross-functional stakeholders to support data-driven initiatives.
What You'll Do
- Design and maintain optimal data pipeline architecture using Azure Data Factory
- Build and manage ETL workflows through Azure Databricks with a strong understanding of the Spark framework
- Assemble large, complex datasets that meet functional and non-functional business requirements
- Build infrastructure for optimal extraction, transformation, and loading of data from diverse sources using SQL and Azure big data technologies
- Create data tools to support analytics and data science teams in optimizing products and workflows
- Work with stakeholders across executive, product, data, and design teams to address data-related technical needs
- Collaborate with data and analytics experts to improve functionality and scalability of data systems
What You Bring
- Hands-on experience with Azure Data Factory, Azure Databricks, and Azure Machine Learning
- Strong PySpark and SQL skills with a solid understanding of the Spark framework
- Proficiency in Python for data engineering and machine learning workflows
- Familiarity with Azure security practices and DevOps pipelines
- Experience working with cloud platforms including AWS and Snowflake is an asset
- Strong communication skills with the ability to work across technical and non-technical stakeholders
- Eligibility for a mandatory background check
Nice to have
- Experience with Power BI for analytics and reporting
- Familiarity with DevOps practices for data pipeline deployment and management
- Prior experience in a regulated or enterprise-scale data environment
Work setup
- Onsite in Brampton, ON
- 6+ month contract
- English proficiency required