Director of AI Engineering Operations & Data Engineering, Workday
CA$151.8-227.8k
More information about location
Enterprise AI platform for managing HR and finance
Be an early applicant
Enterprise AI platform for managing HR and finance
1001+ employees
Be an early applicant
CA$151.8-227.8k
More information about location
1001+ employees
Company mission
To leverage the power of AI to elevate humans and supercharge work, moving business forever forward.
Role
Who you are
- 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
- 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
- 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
- Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Business Administration, or a related field. PhD is a plus
What the job involves
- The Enterprise Data and AI Technologies & Architecture (EDATA) organization is a dynamic and evolving team that is spearheading Workday’s growth through trusted data excellence, innovation, and architectural thought leadership
- Equipped with an array of skills in data & AI platforms and architecture, data science, engineering, machine learning and AI strategy & product management, this team orchestrates the flow of data across our growing company while ensuring data accessibility, accuracy, and security
- With a relentless focus on innovation and efficiency, Workmates in EDATA enable the transformation of complex data sets into actionable insights that fuel strategic decisions and position Workday at the forefront of the technology industry
- EDATA is a global team distributed across the U.S., Canada and India
- 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
- You'll 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
- 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
- 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
- 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
- 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
Our take
Workday is a cloud-based software vendor that provides management of workforces and finances. The company uses a single database for workforce management and financial management to offer integration and optimize business intelligence across companies. It has added to the packages and tools it offers over the years, providing analytic options that allow companies to combine third-party data with information collected by Workday.
The company has also grown through acquisitions and partnerships to broaden its capabilities.. Most recently, in 2025 it purchases Sana, an AI-driven enterprise knowledge and learning platform, to create a "new front door for work". This acquisition allows Workday to integrate Sana's AI-powered search, agents, and learning capabilities with its own data and workflows, allowing employees to access information, automate tasks, and complete their day entirely within Workday.
Through a combination of strategic acquisitions and in-house development, WOrkday has built a comprehensive suite of HR, financial, and enterprise tools. By focusing on innovation and AI-driven workflows, the company continues to push productivity and decision-making for organizations worldwide. Building on this track record, Workday is very much positioned for even more growth, reinforcing its status as a leader in shaping the future of work.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
16% employee growth in 12 months
Company
Funding (last 2 of 5 rounds)
Oct 2011
$85m
SERIES F
Apr 2009
$75m
SERIES E
Total funding: $215.3m
Company HQ
Pleasanton, CA
Leadership
Aneel Bhusri
(Co-Founder & Executive Chair)Annel began his career at Morgan Stanley as a Corporate Finance Analyst. He then spent nearly 6 years at PeopleSoft as a Senior VP before co-founding Workday in 2005, where he has served as the CEO ever since.
Carl Eschenbach
(CEO)Carl joined Workday in 2022 as Co-CEO, becoming CEO in 2024. He has also been a Partner at Sequoia Capital since 2016. Previously, he spent 14 years at VMware as President and COO and 3 years at Inktomi Corporation as the VP of North America Sales.
Peter Bailis
(CTO)Prior to joining Workday in 2025, People was a VP of Engineering at Google. He also previously founded Sisu Data, where he served as the CEO for over 5 years.
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