Who you are

- 12+ years of professional technical leadership experience in DataevOps, DevOps, cloud automation, program management, or platform engineering tracks within enterprise data and analytics

- 12+ years of experience in managing and scaling a suite of interrelated data platform products, cluster configurations, and CI/CD networks at an enterprise level

- 12+ years of experience performing within leadership presence with a history of influencing VP and SVP-level stakeholders to drive technical consensus and cross-functional organizational pivots

- Contemporary Data Stack &
- Cloud Foundations: Expert-level technical command over high-scale distributed data platforms, capital asset cluster budgeting, modern warehouse layouts, Infrastructure as Code (Terraform), and hyperscale pipeline orchestration boundaries

- Hands-on experience or familiarity with GitHub Actions, Snowflake, Fivetran, Sigma, and Atlan (or similar enterprise data platforms) is preferred

- AI-Native Development &

- Ops: Master-level capability directing AI-forward validation and deployment frameworks, setting branch benchmark policies for autonomous code generation loops, and designing division-level agent networks to eliminate manual infrastructure workflows

- Data Governance &

- Observability: Comprehensive expertise utilizing federated active metadata layers and predictive data trust telemetry to hardcode compliance logic natively into global platform environments and manage complex asset lifecycles

- Operational Communication &

- Collaboration: Superior capacity to successfully navigate high-pressure corporate environments and complex technical landscapes to secure functional consensus across competing business units, acting as an active change agent and thought leader for the DevOps and engineering communities





What the job involves

- As a Principal DataOps Engineer (P5), you serve as a preeminent technical authority, strategic leader, and primary architect of Workday’s data platform program execution and methodology deployment

- Operating at the highest tier of individual contribution, you define the long-term vision, core execution standards, and multi-quarter roadmaps for a mission-critical infrastructure portfolio, ensuring our platforms are structurally positioned to support Workday's hyper-growth trajectory

- You resolve high-level technical ambiguity, mitigate existential architecture risks, and lead complex multi-team transformations to deliver data-as-a-product assets at scale

- You sit at the center of Workday's AI-forward operating model, defining and governing the structural use of DataOps, Data Product, and Active Data Governance frameworks across the enterprise ecosystem

- You provide the overarching operational blueprints for embedding advanced AI capabilities into our continuous delivery lines, building language model solutions and automated workflows that safely power autonomous workloads

- Concurrently, you lead the transition to an AI-first workforce, designing division-level agent networks inside Sana and Gemini environments to automate routine tasks, manage technical debt, and multiply organization-wide delivery velocity

- Technical Delivery:



Serve as the preeminent technical authority defining the long-term vision, core execution standards, and multi-quarter architecture blueprints for a mission-critical enterprise cloud infrastructure portfolio. Govern global platform administration paradigms and Infrastructure as Code (Terraform) architecture standards and, CICD pipelines, mentoring senior engineers and establishing foundational infrastructure modules across the organization

- Knowledge Management: Establish and govern function-wide knowledge synchronization standards and "Documentation as Code" paradigms across the global DevOps and Analytics Engineering job families to ensure enterprise architectural clarity

- Incident Response &
- Operational Resilience: Mitigate existential infrastructure and architecture risks across the global enterprise. Design high-scale zero-trust data reliability parameters and predictive platform telemetry layers to guarantee unbroken data platform uptime during hyper-growth cycles

- Agile Operational Facilitation: Sponsor and chair cross-functional technical review boards to align technical direction across competing business segments. Drive complex multi-team infrastructure transformations, navigate platform migration blocks, and manage capital resource planning

- ED&A; Methodologies: Establish and govern the core operational blueprints for embedding DataOps and Active Data Governance principles directly into our master software continuous delivery pipelines

- AI Productivity: Pioneer the implementation of an AI-first workforce strategy by building division-level agent networks and automated scripts natively inside Cursor IDE, Sana, and Gemini tracks to automate code refactoring, system validation, and portfolio tracking at an enterprise scale

📌 Principal DataOps Engineer (Toronto)
🏢 Workday
📍 Toronto