Principal DataOps Engineer – DataOps Engineering

Job Description

Principal DataOps Engineer | Workday

The Tone:
This is a full-time role at Workday, located in Pleasanton, California, with a hybrid work model. Workday is a Fortune 500 company and a leading AI platform for managing people, money, and agents, focused on shaping the future of work. This role is crucial for Workday’s new Enterprise Data and Analytics (ED&A) team, tasked with transforming how the company creates and shares trusted data to drive actionable insights and innovation. As a Principal DataOps Engineer, you will serve as a preeminent technical authority, defining the vision and architecture for mission-critical data infrastructure, positioning Workday at the center of an AI-forward operating model.

The TL;DR
• Role: Full Time
• Location: Hybrid – Pleasanton, California, USA
• Pay: $147300–$263200 yearly
• Team: Enterprise Data and Analytics (ED&A) team
• Mission: Define the long-term vision, core execution standards, and multi-quarter roadmaps for mission-critical infrastructure, ensuring platforms support Workday’s hyper-growth trajectory.
• Tech Stack: Terraform, GitHub Actions, Snowflake, Fivetran, Sigma, Atlan

What You’ll Actually Do
• Technical Delivery: Define the long-term vision, core execution standards, and multi-quarter architecture blueprints for a mission-critical enterprise cloud infrastructure portfolio.
• Governance & Standardization: Govern global platform administration paradigms, Infrastructure as Code (Terraform) architecture standards, and CI/CD pipelines across the organization.
• Operational Resilience: Mitigate existential infrastructure and architecture risks, designing high-scale zero-trust data reliability parameters and predictive platform telemetry layers.
• Strategic Facilitation: Sponsor and chair cross-functional technical review boards to align technical direction across competing business segments and drive complex infrastructure transformations.
• AI Productivity: Pioneer an AI-first workforce strategy by building division-level agent networks and automated scripts within environments like Cursor IDE, Sana, and Gemini for enterprise-scale automation.

The Must-Haves
• Background: Principal level technical leader in DataOps, DevOps, cloud automation, program management, or platform engineering tracks within enterprise data and analytics.
• Experience: 12+ years in technical leadership, 12+ years managing and scaling interrelated data platform products, cluster configurations, and CI/CD networks, and 12+ years influencing VP and SVP-level stakeholders.
• Skills: Expert-level technical command over high-scale distributed data platforms, modern warehouse layouts, and hyperscale pipeline orchestration boundaries, including Infrastructure as Code (Terraform). Master-level capability in directing AI-forward validation and deployment frameworks, and comprehensive expertise utilizing federated active metadata layers and predictive data trust telemetry for data governance.
• Bonus: Hands-on experience or familiarity with GitHub Actions, Snowflake, Fivetran, Sigma, and Atlan, coupled with a superior capacity to navigate high-pressure corporate environments and secure functional consensus across competing business units.