Sr Analytics 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.

About the Team

About the Role

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. 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. *Position may allow for partial telecommuting.

Salary Range: $160,056 - $216,500

About You

Basic Qualifications

Master's degree in Computer Science, Engineering, Information Technology, or related field plus two (2) years of experience in the job offered or related occupation.

Requires 2 years (24 months) of experience in the following:

• Semantic Engineering;

• Data Analytics;

• Data Architecture;

• Data Engineering;

• Solution Design;

• Data Warehousing; and

• Computer Coding.

Other Qualifications

Bachelor's degree in Computer Science, Engineering, Information Technology, or related field plus five (5) years of experience in the job offered or related occupation.

Requires five years (60 months) of experience in the following:

• Semantic Engineering;

• Data Analytics;

• Data Architecture;

• Data Engineering;

• Solution Design;

• Data Warehousing; and

• Computer Coding.

Workday Pay Transparency Statement

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.

Our Approach to Flexible Work
 

Workday uses a hybrid Flex Work Model. Most roles require at least 50% in-person time each quarter in a Workday office or with customers, prospects, or partners, with specific expectations varying by role, team, country, and business needs.

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