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 solid 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

Bill 5, Protect Ontario by Unleashing Our Economy Act, 2025 , the resource may be partially assigned to Bill 5‑related projects or initiatives on an as‑needed basis.

Responsibilities

Design and develop data pipelines from source systems to end users.

Optimize data pipelines.

General Skills

Experience with cloud data platforms, data management, and data exchange tools and technologies.

Experience with commercial and open‑source data and database development and management, specializing in data storage settings and managing Cloud Data as a Service (DaaS), application Database as a Service (DBaaS), Data Warehouses as a Service (DaaS), and other storage platforms in both cloud and on‑premises environments.





Experience with data pipeline and workflow development, orchestration, deployment, and automation, specializing in programming and pipelines to create and manage data flows and data movement.

Experience as a Cloud Data Engineer, including familiarity with and experience in different programming languages and the ability to integrate multiple platforms to create data pipelines, automate tasks, and write scripts.

Experience with DataOps principles, best practices, implementation, and Agile project development and deployment.

Experience with Continuous Integration/Continuous Development/Deployment (CI/CD) and data provisioning automation.

Experience with digital products, data analysis, data exchange, data provisioning, and data security.

Extensive expert experience in designing, developing, and implementing data conversion and migration of Very Large Data (VLD) across Online Analytical Processing (OLAP) and Online Transaction Processing (OLTP) environments to Cloud Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS) environments.

Experience in the design, development, and implementation of fact/dimension models, data mapping, data warehouses, data lakes, and data lakehouses for enterprise environments.

Experience managing cloud data services for project delivery, including storage, repositories, data lakes, data lakehouses, key vaults, virtual machines, disks, and related services.

Experience with structured, semi‑structured, and unstructured data collection, ingestion, provisioning, and exchange; technological development of enterprise data warehouse, data lake, and data l

📌 – Data Ops/Cloud Data Engineer – Senior (Toronto)
🏢 S M Software Solutions
📍 Toronto