Data Engineer

Tasks

• Develop scalable data ingestion, transformation, and orchestration pipelines using Databricks and Apache Airflow.
• Develop reusable Databricks notebooks, transformation components, and automated data quality checks.
• Perform Spark performance tuning, pipeline troubleshooting, data reconciliation, and workload optimization.
• Collaborate with technical teams and contribute to enterprise data engineering best practices.

Requirements

• 4+ Years
• Strong hands-on experience with Azure Data Factory (ADF), Azure Databricks, Python, PySpark, SQL, and Azure Cloud Services.
• Expertise in Medallion Architecture (Bronze, Silver, Gold) and Delta Lake.
• Strong experience with Azure DevOps, Git, CI/CD pipelines, and automated deployments.
• Knowledge of data governance, metadata management, and Unity Catalog.
• Experience with solution design, code reviews, and mentoring is an added advantage.
• Good to have: Databricks Asset Bundles, REST APIs, and enterprise data platform integrations.

Schedule

• Full-Time
• Onsite

How to apply

• Send your updated resume by email.

Location

• Toronto, ON, Canada