Your work days are brighter here.
At Workday, it all began with a conversation over breakfast. When our founders met at a sunny California diner, they came up with an idea to revolutionize the enterprise software market. And when we began to rise, one thing that really set us apart was our culture. A culture which was driven by our value of putting our people first. And ever since, the happiness, development, and contribution of every Workmate is central to who we are. Our Workmates believe a healthy employee-centric, collaborative culture is the essential mix of ingredients for success in business. That’s why we look after our people, communities and the planet while still being profitable. Feel encouraged to shine, however that manifests: you don’t need to hide who you are. You can feel the energy and the passion, it's what makes us unique. Inspired to make a brighter work day for all and transform with us to the next stage of our growth journey? Bring your brightest version of you and have a brighter work day here.
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About the Team
Workday has launched an Enterprise Data and Analytics (ED&A) Team to Transform and optimize the way Workday creates and shares trusted data to drive actionable insights and data led innovation across the enterprise. To enable this strategy, the ED&A team has worked with the business to identify critical business areas in which data and analytics can make a material difference in the execution of Workday’s strategic goals. Each of these goals is being organized as a data product with a dedicated multi-functional team to drive a diverse set of data management, governance, and data analytics to realize relevant, measurable business change.
As part of ED&A and enabling this strategy, the Analytics Engineering team is at the forefront of transforming data into reliable and insightful assets. We are responsible for building data products, ensuring data quality and governance through version control, and creating best practices for the organization. The team also supports the creation of a unified and consistent view of our key business metrics, empowering data-driven decision-making across the organization and preparing our data for advanced analytical use cases.
About the Role
As the Semantic Modeling Lead, you will be a thought leader who shapes the future of how Workday's data powers AI and next-generation analytics. You will spearhead the design and implementation of our semantic layer, moving beyond traditional BI/Analytics to unlock deeper insights and enable advanced AI applications from our structured enterprise data. This critical role involves architecting sophisticated ontologies and knowledge graphs that bridge raw data with intelligent consumption. You will collaborate closely with data architects, analytics engineers, data governance, data scientists, and business stakeholders to define a unified semantic framework that not only empowers self-service analytics and ensures data consistency, but also fundamentally transforms our data into an AI-ready knowledge base capable of supporting prompt engineering and complex reasoning. Your expertise will be instrumental in establishing a clear, well-documented, and governed semantic layer that drives data-driven decision-making and unlocks the full potential of Workday’s enterprise data for artificial intelligence.
Responsibilities:
Lead the vision, development, implementation, and governance of sophisticated ontologies and knowledge graphs that capture the meaning and relationships within Workday's structured enterprise data.
Architect and integrate the semantic layer to serve as an AI-ready knowledge base, enabling applications such as advanced analytics, prompt engineering for large language models, and intelligent data discovery while ensuring seamless connectivity and holistic data understanding across the enterprise.
Develop standards, guidelines, and best practices for knowledge representation, semantic modeling, and data standardization across Workday to ensure a clear and consistent approach within the enterprise semantic layer.
Establish and refine operational processes for semantic model development, including intake mechanisms for new requirements (e.g., from AI prompt engineering initiatives) and backlog management, ensuring efficient and iterative delivery.
Collaborate closely with our Data Governance team to define policies and influence practices for the creation, evolution, and governance of semantics in an AI-driven environment, ensuring trust and ethical use.
Partner closely with analytics engineers and data architects to deeply understand the underlying data models in Snowflake and develop a profound understanding of our business domains and data entities. Provide strategic guidance on how structured data can be seamlessly transformed, optimized, and semantically enriched for advanced AI consumption and traditional BI/Analytics tools.
Lead the effort to establish and maintain comprehensive documentation for all aspects of the semantic layer, which includes defining and standardizing key business metrics, documenting ontological definitions, relationships, usage guidelines, and metadata for all semantic models, ensuring clarity, consistency, and ease of understanding for all data users.
Evaluate and monitor the performance, quality, and usability of semantic systems, ensuring they meet organizational objectives, external standards, and the demands of AI applications.
Act as a thought leader, constantly evaluating emerging trends in knowledge graphs, semantic AI, prompt engineering, and related technologies to strategically enhance Workday’s capabilities in knowledge representation and data understanding.
About You
The ideal candidate will be a visionary and highly skilled professional with 5+ years of experience in semantic modeling and knowledge representation, with a strong background in AI data readiness.You possess a deep understanding of analytics engineering concepts, data modeling principles, and a proven ability to design and implement well-documented, governed knowledge graphs and semantic layers tailored for AI and BI/Analytics consumption. You excel at bridging technical and business perspectives, collaborating effectively with diverse teams to drive data clarity, consistency, and accessibility for both advanced AI initiatives and traditional self-service analytics within a modern data stack.
Basic Qualifications:
5+ years of hands-on experience in semantic modeling, ontology engineering, knowledge graphs, or related AI data preparation.
3+ years of experience developing data solutions specifically for AI/ML applications leveraging structured data.
3+ years of experience with data warehousing concepts, dimensional modeling, and data governance principles as they relate to structuring data for semantic enrichment.
Proficiency in SQL and experience working with cloud-based data warehouses, preferably Snowflake.
Strong analytical and problem-solving skills with a keen attention to detail and the ability to translate complex business concepts into logical ontologies and knowledge graph structures.
Other Qualifications:
Hands-on experience with knowledge graph platforms or semantic modeling tools
Experience with enterprise semantic platforms like Cambridge Semantics, AtScale (for BI consumption), or similar.
Experience in applying semantic technologies to support AI/ML initiatives, such as natural language understanding, intelligent search, or reasoning engines.
Familiarity with prompt engineering concepts and how knowledge bases can enhance LLM performance.
Demonstrated ability to establish robust processes for semantic model development, including managing a backlog of requirements and driving iterative improvements.
Prior experience influencing data governance strategies for semantic assets in an AI-driven environment.
Familiarity with data visualization tools (e.g., Sigma, Tableau, Power BI) and how semantic layers can enhance their capabilities, particularly for complex data relationships.
Understanding of Data Governance and Data Management, supported by industry certifications (e.g. DAMA CDMP, DCAM).
Experience in defining and implementing data quality frameworks, particularly in the context of knowledge graphs and semantic models.
Experience working with Agile or Scrum methodologies.
Bachelor's degree in Computer Science, Engineering, Data Science, Information Science, Linguistics, or a related quantitative field.
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 candidate’s 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 Workday’s comprehensive benefits, please click here.
Primary Location: USA.GA.Atlanta
Primary Location Base Pay Range: $144,300 USD - $216,500 USD
Additional US Location(s) Base Pay Range: $137,100 USD - $243,600 USD
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.
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.
Are you being referred to one of our roles? If so, ask your connection at Workday about our Employee Referral process!
