Senior Platform Engineer - Scotiabank, Toronto

AI Summary

The Senior Platform Engineer at Scotiabank in Toronto, Ontario, plays a critical role within the Enterprise Data & AI Technology organization. This position is responsible for building, tuning, and managing infrastructure, DevOps, and site reliability for Data & AI platforms. Key duties include enhancing new features on Azure and Databricks platforms and ensuring technical direction for networking and security architecture. Top requirements include 15+ years of IT experience, with at least 5 years hands-on experience in Microsoft Azure, Databricks on Azure, Infrastructure as Code using Terraform, and CI/CD practices.

Role Overview and Technical Leadership at Scotiabank

As a Senior Platform Engineer at Scotiabank, this role is integral to the Enterprise Data & AI Technology organization, a cornerstone of the bank's strategic initiatives aimed at fostering data-enabled decision-making and AI innovation. The successful candidate will provide clear guidance and direction to the team, aligning goals with the overall Azure and Databricks Platform roadmap and enterprise standards. A significant aspect of this position involves owning the technical direction across Azure and Databricks, encompassing Azure networking and security architecture, including VNets, Private Endpoints, NSGs, route tables, and Azure Firewall. Furthermore, expertise in Azure Identity & Access Management, covering RBAC and PIM, is crucial. The role also demands comprehensive Databricks platform governance, specifically with Unity Catalog, workspace configuration, and cluster policies, ensuring best practices for reliability, cost, and security are consistently applied. This leadership extends to collaborating with cross-functional teams such as IAM, Network, Cloud Ops, and Security partners for seamless integration, process automation, and the delivery of new projects, demonstrating strong management capabilities.

Driving Innovation and Platform Reliability

This Senior Platform Engineer will be at the forefront of continuous process improvements, designing and developing reusable Terraform modules for both Azure native resources and Databricks components like clusters, SQL warehouses, and Unity Catalog objects. These efforts enable consistent, scalable, and automated deployments via Terraform Cloud/Enterprise and CI/CD pipelines, streamlining the management of infrastructure. The role requires advanced monitoring and troubleshooting capabilities to resolve performance issues across Databricks jobs, clusters, and Azure dependencies. Implementing Azure Monitor and Log Analytics-based observability with custom dashboards for cluster/job health and cost insights is key, alongside establishing proactive alerting for early issue detection. Ensuring site reliability is paramount, involving prompt analysis, triage, and resolution of platform issues to meet SLOs. This includes driving error-budget aware practices, post-incident reviews, and resilience engineering. The engineer will also lead incident response, communications, and root-cause analysis, providing critical support during major incidents, including after-hours. Developing logging and monitoring solutions for early detection and actionable insights, standardizing ingestion to Log Analytics from Databricks and key Azure resources, and building dashboards and alert rules are essential for reducing Mean Time To Resolution. Release control management involves maintaining and enhancing the Infrastructure & Platform release pipeline using Terraform, Azure DevOps, and GitHub Actions, enforcing approvals and automated checks for safe, repeatable releases. Credential security is managed through Azure Key Vault and HashiCorp Vault integration with Databricks secret scopes, enforcing least-privilege access via Azure RBAC. Collaboration with Microsoft and Databricks support teams is also a key aspect of platform management.

Essential Skills and Professional Experience

To succeed in this challenging role, candidates must possess extensive professional experience, including over 15 years of IT experience within large organizations operating across various geographies and regulations. A minimum of 5 years of hands-on experience with Microsoft Azure is required, specifically covering networking, security, identity, storage, compute, and PaaS services. Additionally, 5 years of practical experience with Databricks on Azure, encompassing workspaces, jobs/workflows, clusters/SQL warehouses, and Unity Catalog governance, is essential. Proficiency in Infrastructure as Code is critical, with at least 5 years using Terraform modules and Terraform Cloud/Enterprise. Strong command of CI/CD practices, including automated testing, security scanning, and policy gates, gained over 5 years, is also a prerequisite. The role demands 5 years of experience with development and scripting languages such as Python, Go (optional), Bash, or PowerShell for automation and platform tooling. Familiarity with container technologies like Docker and orchestration on AKS or containerized jobs on Databricks is expected, also with 5 years of experience. A deep understanding of Azure networking, RBAC/PIM, and zero-trust principles is crucial for maintaining robust security. In-depth knowledge of various data platforms, including Azure SQL, Cosmos DB, and Databricks Lakehouse, is also necessary. A Bachelor’s degree in computer science, Engineering, Mathematics, or a related management field is required.