DataOps Engineer

Your work days are brighter here. We’re obsessed with making hard work pay off, for our people, our customers, and the world around us. As a Fortune 500 company and a leading AI platform for managing people, money, and agents, we’re shaping the future of work so teams can reach their potential and focus on what matters most. The minute you join, you’ll feel it. Not just in the products we build, but in how we show up for each other. Our culture is rooted in integrity, empathy, and shared enthusiasm. We’re in this together, tackling big challenges with bold ideas and genuine care. We look for curious minds and courageous collaborators who bring sun-drenched optimism and drive. Whether you're building smarter solutions, supporting customers, or creating a space where everyone belongs, you’ll do meaningful work with Workmates who’ve got your back. In return, we’ll give you the trust to take risks, the tools to grow, the skills to develop and the support of a company invested in you for the long haul. So, if you want to inspire a brighter work day for everyone, including yourself, you’ve found a match in Workday, and we hope to be a match for you too.

In 2024, Workday launched the Enterprise Data and Analytics (ED&A) team with a mission to transform and optimize the way Workday creates and shares trusted data to drive actionable insights and data-led innovation across the enterprise.

As a DataOps Engineer, you own the end-to-end delivery and operational uptime of ED&A infrastructure projects. You drive the alignment between complex technical requirements and business outcomes, ensuring that cloud-native automation solutions are built to spec and on time. Operating with technical autonomy, you serve as a master practitioner of DataOps, leading engineering squads through complex sprints while proactively identifying and mitigating delivery risks. You act as a catalyst for modern craft within the infrastructure lifecycle, designing and refining AI-augmented workflows to boost system quality and throughput. You build the automated structures necessary to support AI-enabled data workloads, utilizing advanced co-pilots to eliminate manual environment tracking and scale functional execution capacity.

Technical Delivery: Own the end-to-end configuration, platform delivery, and deployment architectures for data infrastructure and orchestration pipelines across Snowflake, Fivetran, and dbt tracks. Drive cloud platform administration independently using Infrastructure as Code ( Terraform ) to provision, scale, and govern cloud environments safely across deployment targets. Knowledge Management: Architect and mandate modular documentation frameworks across multiple shared repositories. Ensure all active environments, pipeline rules, and system configurations are fully audited and visible across engineering nodes. Incident Response & Operational Resilience: Own operational uptime and proactive risk mitigation for core data environments. Build advanced pipeline health observability patterns inside Acceldata to capture anomalies and eliminate platform downtime processing risks. Agile Operational Facilitation: Lead multi-disciplinary technical squads through complex engineering sprints. Manage pipeline release cadences independently, balance environment resource constraints, and resolve cross-functional roadblock metrics. ED&A Methodologies: Operationalize and enforce DataOps validation frameworks natively across continuous integration pipelines, ensuring the infrastructure framework cleanly yields certified datasets to support enterprise agentic AI readiness. AI Productivity: Design, refine, and embed automated AI-augmented validation workflows, code refactoring templates, and agentic prompting chains inside your own workspace environment to maximize team capacity and delivery speed.

Basic Qualifications: 5+ years of experience in Development Operations or Data