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

Must-Have Requirements

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

Nice-to-Have Skills

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 workplace

Ability to adapt to changing project priorities and tight delivery timelines

Work Environment 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.

Final role details, responsibilities, and terms will be confirmed with shortlisted candidates. Compensation may vary based on experience. Errors and omissions excepted.

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