Senior DataOps/Cloud Data Engineer - Toronto
A 6-month, fully onsite contract in Toronto (via Randstad) to design, build, and automate enterprise ETL/ELT pipelines and Databricks-based data lakehouses, including Oracle-to-Azure data migrations, Unity Catalog governance, and Azure DevOps CI/CD automation.
- Compensation
- Not disclosed
- Location
- Toronto, Canada
- Work setup
- Onsite
- Seniority
- Senior
- Employment
- Contract
- Experience
- Not specified
- Category
- Data engineering
- Posted
Skills
Must have
- Proven experience designing, building, automating, and optimizing complex ETL/ELT processes using Databricks, Delta Live Tables (DLT), and PySpark
- Experience building unified data platforms using Databricks and Unity Catalog
- Strong background with relational databases (Oracle, MySQL, SQL Server), dimensional data modeling, and advanced SQL (PL/SQL, T-SQL) query tuning
- Proficient in creating Azure Data Factory pipelines and custom Databricks pipelines with Azure DevOps Git CI/CD integration
- Proven experience conducting cross-platform data migration and integration (e.g., Oracle to Azure Data Lake, Databricks, or Microsoft Fabric)
Nice to have
- Experience designing Medallion architecture data lakehouses (Bronze, Silver, Gold layers)
- Proficiency with scripting languages (Python, Unix shell, Scala) and cloud platforms (Azure, AWS, GCP)
- Experience with disaster recovery, failover handling, and troubleshooting large-scale OLAP/OLTP systems
Full description
We are seeking an experienced Senior DataOps/Cloud Data Engineer to design, build, automate, and optimize enterprise-grade data pipelines and unified data platforms. In this role, you will lead the end-to-end development of ETL/ELT processes, modern Medallion architecture data lakehouses, and cross-platform data migrations using Databricks, Delta Live Tables (DLT), PySpark, and Azure Data Factory. Working closely with cross-functional technical teams in an Agile environment, you will implement DataOps practices, build CI/CD automation pipelines in Azure DevOps, execute database performance tuning, and establish secure data governance using Unity Catalog.
Location: Toronto, ON (Fully Onsite – 5 days/week required)
Duration: 6-month contract.
Advantages
- Next-Gen Cloud Stack: Direct engineering with Databricks, Delta Live Tables, PySpark, Unity Catalog, and Microsoft Fabric.
- Large-Scale Data Migration: Lead high-visibility enterprise data transformations and cross-platform migrations from legacy Oracle to Azure Cloud environments.
- Automated DataOps & CI/CD: Hands-on ownership of automated pipeline creation, Git integrations, and continuous deployment workflows.
- Dedicated Onsite Synergy: Collaborate directly alongside senior data leads, architects, and engineers in a focused 5-day per week Toronto workspace.
Responsibilities
- ETL/ELT Engineering & Orchestration: Design, build, automate, and optimize complex data extraction, transformation, and loading (ETL/ELT) processes using Databricks, Delta Live Tables (DLT), and PySpark.
- Unified Data Platform Architecture: Develop and manage unified enterprise data lakehouse platforms utilizing Databricks and Unity Catalog for governance, data security, and lineage.
- Data Migration & Integration: Execute large-scale cross-platform data migrations and integrations, moving Very Large Datasets (VLD) from legacy relational systems (Oracle, SQL Server) to cloud destinations (Azure Data Lake, Databricks, Microsoft Fabric).
- Cloud Pipeline Automation & CI/CD: Create, configure, and orchestrate Azure Data Factory copy pipelines and custom Databricks workflows with integrated Azure DevOps Git CI/CD deployment pipelines.
- Database & Dimensional Modeling: Perform relational and dimensional data modeling (fact/dimension tables), schema design, advanced SQL querying (PL/SQL, T-SQL), and query optimization across cloud and on-premise relational databases.
- DataOps & Performance Monitoring: Implement DataOps principles, continuous integration, automated data provisioning, performance monitoring, and query tuning to ensure high availability and scalability.