RQ11486 – Data Ops/Cloud Data Engineer – Senior
Senior contract role (via staffing vendor) for Ontario's Ministry of Public and Business Service Delivery, onsite in Toronto: designing, automating and optimizing enterprise ETL/ELT pipelines and cloud data platforms using Databricks, DLT, Unity Catalog, Azure Data Factory, PySpark and advanced SQL, with Oracle-to-Azure/Databricks/Fabric migrations.
- Compensation
- Not disclosed
- Location
- Toronto, Canada
- Work setup
- Not specified
- Seniority
- Senior
- Employment
- Not specified
- Experience
- Not specified
- Category
- Data engineering
- Posted
Skills
Must have
- Design, build, automate and optimize complex ETL/ELT pipelines using Databricks, Delta Live Tables (DLT) or equivalent
- Develop unified data platforms using Databricks and Unity Catalog or equivalent
- Relational databases: Oracle, MySQL, SQL Server; relational/dimensional data modelling, query optimization, replication, DBA
- Advanced SQL including PL/SQL and T-SQL
- Big data processing with PySpark
- Azure Data Factory pipelines and custom Databricks pipelines with CI/CD via Azure DevOps Git integration
- Data migration and integration across Oracle, Azure Data Lake, Databricks, Microsoft Fabric
- DataOps principles, best practices and Agile project development
- CI/CD and data provisioning automation
- Experience with cloud data platforms, data management and data exchange tools
- Managing cloud data services: storage, repositories, data lakes, key vaults, virtual machines
- Large-scale data conversion/migration across OLAP/OLTP to SaaS/PaaS/IaaS environments
- Fact/dimension models, data mapping, data warehouses, data lakes and lakehouses
- DataOps performance monitoring and tuning
- Strong analytical, problem-solving, communication, presentation and interpersonal skills
- Work onsite in Toronto 5 days per week
Nice to have
- Data lake/lakehouse design and development using medallion architecture
- Advanced hands-on experience with Oracle databases, Azure SQL Server and Azure Data Factory
- Experience with Azure, Google Cloud and AWS
- PL/SQL-based ETL management: troubleshooting, performance tuning, failover, recovery
- Scripting with Python, Unix shell and Scala
- Public sector experience relevant to the Government of Ontario
Full description
Client: Ministry of Public and Business Service Delivery and Procurement – RQ11486
We are seeking a Senior Data Ops/Cloud Data Engineer with extensive experience in designing, developing, automating, and optimizing complex data pipelines and cloud-based data platforms. The ideal candidate will have strong hands‐on expertise in Databricks, Delta Live Tables (DLT), Unity Catalog or equivalent technologies, Azure Data Factory, advanced SQL, PySpark, data modelling, and enterprise‐scale data migration and integration. The successful candidate will be responsible for building and optimizing ETL/ELT processes, implementing CI/CD practices, managing cloud data services, and supporting data engineering initiatives across multiple platforms, including Oracle, Azure Data Lake, Databricks, and Microsoft Fabric.
Role Snapshot
- Job Title: RQ11486 – Data Ops/Cloud Data Engineer – Senior
- Client: Ministry of Public and Business Service Delivery and Procurement
- Work Location: 40 St. Clair Avenue West, Toronto, Ontario, Canada
- Work Arrangement: Onsite – 5 Days per Week
- Estimated Start Date: October 5, 2026
- Estimated End Date: March 31, 2027
- Business Days: 123.00
- Extension: 60.00
- Hours: 7.25 hours per day
- Security Level: No Clearance Required
Must Have
- Experience designing, building, automating, and optimizing complex data ETL/ELT processes using Databricks, Delta Live Tables (DLT), or equivalent technologies.
- Experience developing unified data platforms using Databricks and Unity Catalog or equivalent technologies.
- Experience with relational databases, including Oracle, MySQL, and SQL Server; relational and dimensional data modelling; advanced SQL; query optimization; data replication; and database administration.
- Advanced SQL skills, including PL/SQL and T‑SQL.
- Experience with big data processing frameworks, including PySpark.
- Proficiency in creating Azure Data Factory pipelines for copy activities and developing custom data pipelines in Databricks with CI/CD using Azure DevOps Git integration.
- Experience with data migration and integration across different platforms, including:
- Oracle to Azure Data Lake
- Oracle to Databricks
- Oracle to Microsoft Fabric
Description
To respond to the priorities of the Government of Ontario through the passage of , the resource may be partially assigned to Bill 5‑related projects or initiatives on an as‑needed basis.