Director, AI Engineering Operations & Data Engineering

Your work days are brighter here.

Were 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 were shaping the future of work so teams can reach their potential and focus on what matters most. The minute you join youll 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. Were 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 youre building smarter solutions supporting customers or creating a space where everyone belongs youll do meaningful work with Workmates whove got your return well 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 youve found a match in Workday and we hope to be a match for you too.

About the Team

About the Role

Workday is seeking a Director AI Engineering Operations & Data Engineering who will be a critical leader within the Enterprise Data & AI Technologies and Architecture (EDATA) organization at Workday. This role oversees the strategic direction and execution of both our core Data Engineering & Integrations function and a newly formed AI Engineering Operations function. Youll ensure the scalable reliable and efficient flow of data and the seamless deployment and operation of our AI models serving as a key partner to our internal business stakeholders.

This role requires a leader with deep expertise in modern data architectures/frameworks cloud-native platforms (AWS Snowflake Databricks etc.) and the emerging field of MLOps/AIOps. You must be adept at building and managing high-performing engineering teams driving complex technical roadmaps and building both technical and business relationships across the organization.

Job Duties:

Leadership & Strategy

• Define and champion the vision strategy and roadmap for Data Engineering Integrations and AI Engineering Operations.

• Lead mentor and grow a diverse team of data engineers integration specialists and AI/MLOps engineers fostering a culture of innovation reliability and ownership.

• Partner with the VP of EDATA and other EDATA Directors (Data Platforms Data SRE AI Strategy etc.) to ensure a cohesive and well-governed enterprise data and AI ecosystem.

Data Engineering & Integrations

• Oversee the design development and maintenance of robust scalable and high-performance ETL/ELT data pipelines utilizing platforms like Snowflake and Databricks.

• Ensure data quality integrity and security standards are strictly enforced within all data pipelines and integrations.

• Manage the strategy and execution of all enterprise data integrations connecting core business systems (e.g. Sales Finance HR) to the central data platforms.

AI Engineering Operations (AIOps/MLOps)

• Establish and lead the new AI Engineering Operations function defining its processes best practices and technology stack.

• Implement and manage the MLOps lifecycle including model training orchestration continuous integration/continuous deployment (CI/CD) for models and automated testing.

• Design and provision the production environment for AI models ensuring scalability low-latency inference and seamless integration with end-user applications.

• Collaborate with Data Platforms Data Science & Innovation and AI Architecture to industrialize experimental models into reliable production-ready services.

Operational Excellence

• Work closely with Data SRE (Change Management QA Monitoring) to implement best practices for pipeline and model observability alerting and incident response.

• Ensure the team adheres to architectural standards (defined by the Data & Analytics Architecture team) and security policies (defined by the Data & Analytics Security Architecture team).

• Manage project portfolios resource allocation and budget for both Data Engineering and AI Engineering Operations.

About You

Basic Qualifications:

• 10 years of experience in data engineering software engineering or a related technical field.

• 10 years of expertise with major cloud platforms (AWS Snowflake Databricks) and their ecosystems.

• 7 years of experience managing and leading high-performing engineering teams including managers.

• Proven experience in designing and scaling complex enterprise-level ETL/ELT pipelines.

• Experience building and leading an MLOps/AI Engineering Operations function.

• Deep familiarity with MLOps tools and methodologies (e.g. MLflow Kubeflow Sagemaker/Azure ML/GCP Vertex AI equivalents).

• Strong understanding of Data and AI Architecture principles and a commitment to secure governed data practices.

• Proven track record of developing and implementing data engineering and AI Engineering Ops strategies and frameworks in a corporate environment.

Other Qualifications:

• Excellent communication and presentation skills with the ability to articulate complex technical concepts to non-technical stakeholders.

• Leadership and team management experience with the ability to inspire and develop talent.

• Experience working with cross-functional teams and managing complex projects.

• Deep understanding of AI technologies machine learning models and data analytics.

• Strong strategic thinking and problem-solving skills.

• Bachelors or Masters degree in Computer Science Data Science Artificial Intelligence Business Administration or a related field. PhD is a plus.

Workday Pay Transparency Statement

The annualized base salary ranges for the primary location and any additional locations are listed below. Workday pay ranges vary based on work location. As a part of the total compensation package this role may be eligible for the Workday Bonus Plan or a role-specific commission/bonus as well as annual refresh stock grants. Recruiters can share more detail during the hiring process. Each candidates compensation offer will be based on multiple factors including but not limited to geography experience skills job duties and business need among other things. For more information regarding Workdays comprehensive benefits please click here.

Our Approach to Flexible Work

With Flex Work were 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 youll 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.

Pursuant to applicable Fair Chance law Workday will consider for employment qualified applicants with arrest and conviction records.

Workday is an Equal Opportunity Employer including individuals with disabilities and protected veterans.

At Workday we are committed to providing an accessible and inclusive hiring experience where all candidates can fully demonstrate their skills. If you require assistance or an accommodation at any point please email .

Are you being referred to one of our roles If so ask your connection at Workday about our Employee Referral process!

At Workday we value our candidates privacy and data security. Workday will never ask candidates to apply to jobs through websites that are not Workday Careers.

Please be aware of sites that may ask for you to input your data in connection with a job posting that appears to be from Workday but is not.

In addition Workday will never ask candidates to pay a recruiting fee or pay for consulting or coaching services in order to apply for a job at Workday.