Senior DataOps / Cloud Data Engineer

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

Opens LinkedIn

Employment type: Contract
Experience level: Senior · 8+ 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 enterprise-scale ETL/ELT pipelines and cloud data platforms using Databricks, Azure Data Factory, and related Azure services. Lead data migrations from Oracle and maintain secure, reliable data warehouses, lakes, and lakehouse solutions while implementing DataOps and CI/CD practices.

Job details

The client is seeking a highly experienced Senior DataOps / Cloud Data Engineer to design, develop, automate, optimize, and maintain enterprise-scale data pipelines and cloud-based data platforms. The role focuses on building scalable ETL/ELT processes, developing unified data platforms, implementing enterprise data lakehouse solutions, and migrating complex data environments from traditional databases to modern cloud platforms. Key Responsibilities Design, develop, automate, and optimize scalable ETL/ELT data pipelines using Databricks, Delta Live Tables (DLT), and Azure Data Factory. Build and maintain unified cloud data platforms using Databricks and Unity Catalog. Develop enterprise data warehouses, data lakes, and lakehouse solutions using medallion architecture. Lead data migration and integration from Oracle to Azure Data Lake, Databricks, and Microsoft Fabric. Develop and optimize SQL queries, relational and dimensional data models, and large-scale data processing workflows. Implement CI/CD pipelines, DataOps practices, and deployment automation using Azure DevOps and Git. Monitor, troubleshoot, and optimize data pipeline performance, reliability, and security. Must-Have Skills 8+ years of experience in data engineering, cloud data platforms, and ETL/ELT development. Strong hands-on experience with Databricks, Delta Live Tables (DLT), and Unity Catalog. Expertise in Azure Data Factory (ADF) and building custom Databricks pipelines. Advanced proficiency in SQL, PL/SQL, T-SQL, and PySpark. Strong experience with Oracle, SQL Server, MySQL, database optimization, replication, and data modelling. Experience with Azure DevOps, Git integration, and CI/CD automation. Proven experience migrating data from Oracle to Azure Data Lake, Databricks, and Microsoft Fabric. Nice-to-Have Skills Experience designing data lakes and lakehouses using medallion architecture. Advanced knowledge of Oracle, Azure SQL Server, and Azure Data Factory. Exposure to AWS, Google Cloud Platform (GCP), and Azure. Proficiency in Python, Unix Shell scripting, and Scala. Experience with ETL troubleshooting, performance tuning, failover, and disaster recovery. Familiarity with DataOps best practices, cloud data governance, and enterprise data warehousing. Previous experience working on public sector or government projects.

What you’ll do

Requirements

Requires 8+ years of data engineering and cloud data platform experience, with strong hands-on expertise in Databricks, Delta Live Tables, Unity Catalog, Azure Data Factory, SQL, PL/SQL, T-SQL, and PySpark. Candidates must also have experience with relational databases, data modeling, Azure DevOps, CI/CD, and migrating Oracle data to Azure Data Lake, Databricks, and Microsoft Fabric.