Lead, Data Engineering (2025-377-CS)
at
WoodGreen Community Services
Toronto, ON, Canada
-
Full Time
Start Date
Immediate
Expiry Date
20 Sep, 25
Salary
77000.0
Posted On
09 Aug, 25
Experience
7 year(s) or above
Remote Job
Yes
Telecommute
Yes
Sponsor Visa
No
Skills
Good communication skills
Industry
Information Technology/IT
Description
Responsibilities
Design and operate data platform infrastructure in Azure in collaboration with IT, ensuring deployments align with organizational standards for security, scalability, and governance.
Provision and configure core platform services including Azure Data Factory, Microsoft Fabric, Azure SQL, Synapse, Data Lake Gen2, and Databricks.
Build and maintain automated ingestion and transformation pipelines, embedding observability, failover handling, and performance optimization.
Implement and document Infrastructure-as-Code (IaC) using tools such as Terraform, Bicep, or ARM templates.
Develop and maintain automated deployment pipelines (CI/CD) using Azure DevOps for data engineering solutions and infrastructure as code.
Enforce data role-based access controls (RBAC), encryption standards, and identity boundary rules in accordance with governance guidance.
Collaborate with the Lead, Data Governance to embed metadata capture, lineage tracing, and data validation into system pipelines.
Partner with the Data & Insights function to deliver curated, high-performance datasets that power semantic models and enterprise dashboards in Power BI.
Monitor platform health, resolve issues proactively, and implement improvements to enhance performance, optimize costs, and ensure high reliability.
Lead platform hardening activities including penetration test response, network policy enforcement, and service principal rotation.
Maintain infrastructure logs, system health reports, and support audit-readiness documentation for internal and external review.
Act as an escalation point for pipeline failures, system outages, or data delivery delays, with a mandate to resolve or coordinate cross-team recovery.
Provide mentorship and on-the-ground support for technical staff or external engineering partners.
Represent data engineering at architectural planning meetings, tool evaluations, and roadmap discussions.
Perform technical gap coverage across all Enterprise Analytics operations as directed by the Director, including ad hoc solution prototyping, tool configuration, and data remediation efforts
Linked-in
Google