DataOps/Cloud Data Engineer
- Toronto, ON, Canada
- Greater Toronto Area, Canada, Canada
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Original job description
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Ref: RQ11576 Contract – 12 Months (Extension Possible) Onsite – Toronto (595 Bay St.)
Posted Date: 2026-10-20
Location: Onsite – Toronto (595 Bay St.)
Public Sector Experience: Required – OPS / Public Sector
Contract End Date: 2027-10-01 *
Rate: $97/hour
Overview
The Ministry of Public and Business Service Delivery and Procurement, through the Government Services Integration Cluster, is seeking a Senior DataOps/Cloud Data Engineer to join their team in Toronto. The successful candidate will design, implement, and support cloud-based data platforms, pipelines, and integration services that enable data governance, quality, and interoperability across enterprise environments. This is a fully onsite, senior-level engagement requiring deep expertise in modern data engineering practices and cloud-native architectures.
Key Responsibilities
This is a fully onsite position, five days per week, based at 595 Bay St., Toronto. No security clearance is required. The team follows Agile project development and deployment practices. The role involves collaboration with architects, data modellers, and governance stakeholders across the Government Services Integration Cluster.
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Ref: RQ11576 Contract – 12 Months (Extension Possible) Onsite – Toronto (595 Bay St.)
Posted Date: 2026-10-20
Location: Onsite – Toronto (595 Bay St.)
Public Sector Experience: Required – OPS / Public Sector
Contract End Date: 2027-10-01 *
Rate: $97/hour
Overview
The Ministry of Public and Business Service Delivery and Procurement, through the Government Services Integration Cluster, is seeking a Senior DataOps/Cloud Data Engineer to join their team in Toronto. The successful candidate will design, implement, and support cloud-based data platforms, pipelines, and integration services that enable data governance, quality, and interoperability across enterprise environments. This is a fully onsite, senior-level engagement requiring deep expertise in modern data engineering practices and cloud-native architectures.
Key Responsibilities
- Design and develop scalable data pipelines and ETL/ELT processes from source systems to end users
- Implement and optimize cloud-based data platforms, including Data Lake, Data Lakehouse, and Data Warehouse architectures
- Develop and maintain integration solutions using APIs, event-driven architectures, and batch or streaming technologies
- Implement DataOps practices including CI/CD pipelines, deployment automation, testing, monitoring, and operational support
- Automate metadata collection, data movement, and operational processes across the platform
- Enable data quality, lineage, and metadata capabilities within cloud data environments
- Support cloud modernization and large-scale data migration initiatives involving OLAP and OLTP environments
- Manage cloud data services including storage repositories, key vaults, virtual machines, and Data Lake configurations
- Collaborate with architects, data modellers, and governance teams to operationalize data standards and common data models
- Perform DataOps performance monitoring, tuning, and troubleshooting of complex technical issues
- Deliver cloud-hosted data products and reusable data services aligned to enterprise data governance and security best practices
- Demonstrated experience designing, implementing, and supporting cloud-based data platforms and services
- Strong experience developing scalable ETL/ELT processes, data pipelines, and integration solutions
- Experience implementing DataOps practices including deployment automation, CI/CD, testing, monitoring, and operational support
- Experience with cloud-native data engineering and modern data platform architectures (SaaS, PaaS, IaaS)
- Experience implementing metadata, lineage, and data quality capabilities within cloud data environments
- Experience developing integration solutions using APIs, event-driven architectures, and batch or streaming technologies
- Experience with Databricks, Delta Lake, and Databricks SQL
- Knowledge of Medallion Architecture
- Experience with Azure Data Services and/or Azure Data Factory
- Experience with Informatica or equivalent enterprise integration platforms
- Experience operationalizing common data models and metadata repositories
- Knowledge of data governance, security, and operational best practices for cloud platforms
- Experience supporting cloud modernization and data migration initiatives
- Strong analytical, organizational, and communication skills with a track record of meeting deadlines
- Experience with Microsoft Fabric and Microsoft Purview
- Experience with graph technologies and semantic repositories
- Knowledge and understanding of AODA and related accessibility standards
- Prior experience in the Ontario Public Sector (OPS) or broader public sector environment
- Ability to adapt to changing project priorities and tight delivery timelines
This is a fully onsite position, five days per week, based at 595 Bay St., Toronto. No security clearance is required. The team follows Agile project development and deployment practices. The role involves collaboration with architects, data modellers, and governance stakeholders across the Government Services Integration Cluster.
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- Final role details, responsibilities, and terms will be confirmed with shortlisted candidates. Compensation may vary based on experience. Errors and omissions excepted.
More about this job
Responsibilities
Design, implement, and support cloud data platforms, scalable pipelines, and integration services, including data lake, lakehouse, and warehouse architectures. Establish DataOps automation and operational practices, support cloud modernization and migration, and enable data quality, lineage, metadata, governance, and secure reusable data products.
Requirements
Requires strong experience building and supporting cloud data platforms, ETL/ELT pipelines, integrations, and DataOps practices, including CI/CD, testing, monitoring, and operational support. Candidates should have experience with Databricks, Delta Lake, Databricks SQL, Medallion Architecture, Azure data services, and enterprise integration platforms, plus knowledge of governance, metadata, and data migration; public-sector experience is required.
Skills
- DataOps
- Cloud Data Engineering
- ETL/ELT
- Data Pipelines
- Databricks
- Delta Lake
- Databricks SQL
- Medallion Architecture
- Azure Data Services
- Azure Data Factory
- Informatica
- Data Governance
- Data Quality
- Metadata Management
- Data Lineage
- API Integration
Visa sponsorship
Not detected in the job text
Categories
- Data & Analytics
- Technology
- Software
- Government & Public Sector
Keywords
- DataOps
- Cloud Data Engineering
- Cloud-Native Architecture
- ETL/ELT
- Data Pipelines
- Data Lake
- Data Lakehouse
- Data Warehouse
- Databricks
- Delta Lake
- Databricks SQL
- Medallion Architecture
- Azure Data Services
- Azure Data Factory
- Microsoft Fabric
- Microsoft Purview
- Informatica
- APIs
- Event-Driven Architecture
- Batch Processing
- Streaming
- CI/CD
- Deployment Automation
- Data Quality
- Data Lineage
- Metadata Repositories
- Data Governance
- Data Migration
- OLAP
- OLTP