DataOps/Cloud Data Engineer - Senior (ETL/Databricks experience)

Toronto, ON
On-site
Posted Oct 17, 2026
1 position

$85–$90 / hour

Opens LinkedIn

Employment type: Contract
Experience level: Senior · 5+ years
Posting language: English
Working hours: 40 hours per week
Seniority: Mid-Senior level
Application method: Direct apply is available

Job summary

Design, build, automate, and optimize complex ETL/ELT processes and unified data platforms using Databricks, Delta Live Tables, and Unity Catalog or equivalent tools. Develop data pipelines and integrations, and migrate data across Oracle, Azure Data Lake, Databricks, and Microsoft Fabric.

Job details

Job Role: DataOps/Cloud Data Engineer - Senior (ETL/Databricks experience) Location : Toronto, ON/Onsite Position Type : Contract Role Start Date 2026-10-05 End Date 2027-03-31 5 days Onsite in a week Ideal Candidate Rate: CAD 85-90/Hr (Depending on the experience) Must Have: Design, build, automate and optimize complex data ETL/ELT processes using Databricks, Delta Live Tables (DLT) and equivalent. Development of unified data platforms using Databricks and Unity catalog or its equivalent. Relational databases (Oracle, MySQL, SQL Server), data modelling (relational & dimensional), advanced SQL, query optimization, data replication, administration. Advanced SQL skills (PL/SQL, TSQL). Big Data processing Frameworks (PySpark). Proficient in creating Azure Data Factory pipelines for copy activity and custom data pipelines in Databricks with CI CD (Azure DevOPS Git Integration) . Data migration and data integration across different platforms Oracle to Azure Data Lake, Oracle to Databricks, Oracle to Microsoft Fabric. Note: AI-enabled tools may be used to sort applications based on job-related criteria. All AI generated results are vetted by our team and the decision of which candidates move forward is always made by a human.

What you’ll do

Requirements

The role requires experience with Databricks, Delta Live Tables, relational databases, relational and dimensional data modeling, advanced SQL, and big data processing with PySpark. Candidates must also be proficient in Azure Data Factory, Azure DevOps Git integration and CI/CD, and data migration and integration across platforms.