DataOps Engineer
AI in this role
Own end-to-end data infrastructure and orchestration while designing AI-augmented workflows for data workloads.
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.
About the Team
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.About the Role
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.
Key Responsibilities
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.
About You
Basic Qualifications:
5+ years of experience in Development Operations or Data Engineering with a focus on cloud-native automation.
Proficient in managing complex workstreams using GitHub, Jira, and Smartsheet.
Proven track record of delivering technical projects in a multinational SaaS environment.
Other Qualifications:
Modern Data Stack & Cloud Foundations: Deep working knowledge of Snowflake data architectures, Infrastructure as Code (Terraform), Fivetran connectivity patterns, and dbt transformation networks to design resilient data movement loops and govern multi-team CI/CD environments. Hands-on experience or familiarity with GitHub Actions, Snowflake, Fivetran, Sigma, and Atlan (or similar enterprise data platforms) is preferred.
AI-Native Development & Ops: Personal mastery of rapid automation prototyping, unit-test automation, and syntax refactoring utilizing Cursor or GitHub Copilot, balanced with design pattern fluency in modern LLM orchestration frameworks.
Data Governance & Observability: Advanced command of metadata classification frameworks within Atlan or similar tools and deep metric configuration experience utilizing modern data observability platforms to manage automated environment visibility, trace data lineage, and enforce data trust boundaries.
Operational Communication & Collaboration: Strong communication and cross-functional alignment skills, uniquely equipped to navigate operational ambiguity, guide technical decisions for engineering pods, and resolve data product constraints across partner domains.
Our Approach to Flexible Work
With Flex Work, we’re combining the best of both worlds: in-person time and remote. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. We know that flexibility can take shape in many ways, so rather than a number of required days in-office each week, we simply spend at least half (50%) of our time each quarter in the office or in the field with our customers, prospects, and partners (depending on role). This means you'll have the freedom to create a flexible schedule that caters to your business, team, and personal needs, while being intentional to make the most of time spent together. Those in our remote "home office" roles also have the opportunity to come together in our offices for important moments that matter.
Workday is committed to providing reasonable accommodations for qualified individuals during our application process, in order to perform one or more essential functions of their job, as well as regarding the use of AI tools for employment decision-making to any degree. Please see below for more details including how to request an accommodation as a qualified veteran, due to a disability or for religious reasons, or as otherwise provided under applicable law.
Workday prohibits taking adverse action against any candidate or employee for reporting a possible violation of this policy, requesting one or more work accommodations, exercising a privacy right, or cooperating in an investigation in accordance with applicable law. Any employee who retaliates against a candidate or employee for doing so may be subject to disciplinary action, up to and including termination of employment, to the fullest extent allowable under applicable law.
If you require a reasonable accommodation, you may email accommodations@workday.com, as far in advance as possible.
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How we rate this
DataOps Engineer at Workday rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- Tell me about a project where dataops was part of your work. What did you do?
- Tell me about a project where infrastructure was part of your work. What did you do?
- Tell me about a project where pipelines was part of your work. What did you do?
- Tell me about a project where automation was part of your work. What did you do?
- Walk me through how you've used Copilot in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: Dataops, Infrastructure, Pipelines, Automation, and Copilot. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.
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