Principal DataOps Engineer (DevOps for Data)

Workday•Pleasanton, CA

6d•$147,300 - $263,200•Hybrid

About The Position

The Principal DataOps Engineer (P5) is a senior individual contributor serving as a technical authority, strategic leader, and architect for Workday’s data platform program execution and methodology deployment. The role defines long-term vision, execution standards, and multi-quarter roadmaps for mission-critical enterprise cloud infrastructure, resolving complex technical ambiguity and architecture risks while leading multi-team transformations to deliver data-as-a-product assets at scale. Within Workday’s Enterprise Data and Analytics organization, the position establishes and governs enterprise frameworks for DataOps, data products, and active data governance. It also develops operational blueprints for embedding AI capabilities into continuous delivery, and advances AI-enabled workflows and agent networks to automate routine work, address technical debt, and increase delivery velocity. The role is open to a 50% hybrid arrangement reporting to the Pleasanton campus; Workday’s flexible work model calls for spending at least half of each quarter in an office or with customers, prospects, or partners, depending on the role.

Requirements

12+ years of professional technical leadership experience in DataOps, DevOps, cloud automation, program management, or platform engineering within enterprise data and analytics.
12+ years of experience managing and scaling interrelated data platform products, cluster configurations, and CI/CD networks at enterprise scale.
12+ years of experience demonstrating leadership and influencing VP- and SVP-level stakeholders to reach technical consensus and drive cross-functional organizational change.
Expert-level technical command of high-scale distributed data platforms, capital asset cluster budgeting, modern warehouse layouts, Infrastructure as Code (Terraform), and hyperscale pipeline orchestration.
Master-level capability directing AI-forward validation and deployment frameworks, setting branch benchmark policies for autonomous code generation loops, and designing agent networks to reduce manual infrastructure workflows.
Comprehensive expertise with federated active metadata layers and predictive data trust telemetry to embed compliance logic in global platform environments and manage complex asset lifecycles.
Strong communication and collaboration skills to secure consensus across competing business units and act as a change agent and thought leader for DevOps and engineering communities.

Nice To Haves

Hands-on experience or familiarity with GitHub Actions, Snowflake, Fivetran, Sigma, and Atlan or similar enterprise data platforms.

Responsibilities

Define the long-term vision, execution standards, and multi-quarter architecture blueprints for an enterprise cloud infrastructure portfolio.
Govern global platform administration practices, Terraform Infrastructure as Code architecture standards, and CI/CD pipelines; mentor senior engineers and establish foundational infrastructure modules.
Establish and govern function-wide knowledge synchronization and Documentation as Code standards across DevOps and Analytics Engineering job families.
Mitigate infrastructure and architecture risks across the enterprise; design zero-trust data reliability parameters and predictive platform telemetry to support data platform uptime.
Sponsor and chair cross-functional technical review boards, align technical direction across business segments, lead multi-team infrastructure transformations, address platform migration obstacles, and manage capital resource planning.
Establish operational blueprints for embedding DataOps and Active Data Governance into master software continuous delivery pipelines.
Build AI-enabled agent networks and automated scripts in Cursor IDE, Sana, and Gemini environments to automate code refactoring, system validation, and portfolio tracking.