At Yum!, we’re hiring a Data Architect to help shape how we model, optimize, and scale data across a globally distributed enterprise. In this role, you’ll lead dimensional modeling efforts across domains, champion best practices, and continuously improve the standards that guide our data and BI ecosystem. You’ll be the go-to expert for data warehouse dimensional modeling and database performance tuning, partnering closely with data engineers, BI developers, and technical stakeholders worldwide. We’re looking for someone who excels in collaboration and communication—able to gather requirements, facilitate alignment across teams, and translate business questions into high-quality, durable data designs. Having this person also open and able to use existing AI capability and features to assist their day-to-day is strongly encouraged.

• Proven experience delivering dimensional models for enterprise analytics using Snowflake and/or similar cloud data platforms.
• Strong Familiarity with Power BI or similar consumption patterns and designing models for BI performance and usability.
• Excellent collaboration and communication skills as this role will be gathering requirements, working cross functionally, discussing complex topic with various business units across the globe.
• Experience supporting or designing analytics solutions consumed in Power BI (semantic layer considerations, performance patterns, star schema best practices).
• Strong Experience designing Semantic Models
• Strong Experience with enterprise modeling tools such as Erwin, ER/Studio, or comparable platforms, with the ability and desire to become an expert in SQLDBM.
• Background implementing or influencing data governance, modeling review boards, metadata standards, lineage/documentation practices, or data quality frameworks.
• Experience working in complex organizations with multiple domains, systems, and stakeholder groups, successfully driving alignment across teams.
• Exposure to modern data engineering practices (CI/CD for data, automated testing, version control, environment promotion patterns).

Nice to Haves:

• Experience establishing model governance practices (review boards, version control, documentation, naming standards, lineage/metadata).
• Familiarity with data transformation patterns and modern data engineering workflows (CI/CD, code reviews, automated testing).
• Experience implementing or influencing data quality frameworks, reconciliation strategies, and proactive monitoring.
• Background working in global, multi-domain enterprise environments with multiple warehouses/data domains.

Remote role with quarterly travel expectation

Salary Range: 137,900 - 158,300

Benefits: Employees (and their eligible family members) may enroll in the following types of insurance coverage: medical, dental, vision, legal, and accidental death and dismemberment, as well as FSA/HSA (depending on enrolled medical plan). Yum! also provides short-term disability, long-term disability, and life insurance. Employees may enroll in our 401(k) plan. Yum! provides 4 weeks of vacation, paid sick leave, 10 paid holidays, a floating day off, half day Fridays year-round and 2 paid days for volunteer time each calendar year. To learn more about working at Yum! -Click here.

At Yum!, one of our core values is to Believe in ALL People. This means seeing the value in everyone and unlocking their full potential to be their best self. YUM! Brands, Inc. (including its subsidiaries Yum Restaurant Services Group, LLC (“YRSG”) and Yum Connect, LLC (“Yum Digital and Technology”)(collectively, “Yum”) is proud to be an equal opportunity employer and is committed to equity, inclusion, and belonging for all dimensions of diversity. We do not discriminate based on race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability status, age, or any other protected characteristic. Yum! is committed to working with and providing reasonable accommodation to applicants with disabilities or special needs.

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Enterprise Data Modeling Leadership:

• Own end-to-end enterprise data modeling for analytics use cases, from concept through logical and physical design, ensuring consistency and scalability across domains.
• Lead dimensional modeling efforts using Kimball methodologies (facts, dimensions, conformed dimensions, SCDs, grain definition, surrogate keys, etc.) to support enterprise reporting and analytics.
• Partner with business unit architects and engineers to define and standardize shared architecture patterns.
• Design, review, and govern enterprise-scale data models to support our business intelligence layer.
• Apply medallion architecture principles (bronze/silver/gold) to ensure raw-to-curated data lifecycle mapping, including modeling at the appropriate layer and enforcing design intent across stages.
• Explore and evaluate AI capabilities in tooling to determine if it will strengthen the quality of work.

SQLDBM Ownership and Expertise:

• Create and maintain conceptual, logical, and physical models in SQLDBM.
• Help define modeling patterns, templates, naming conventions, and reusable standards within SQLDBM. Championing the use of existing features to further standardization is highly desirable.
• Mentor teammates and promote consistent adoption of SQLDBM across projects.

Best Practices and Standards Development:

• Bring and apply best practices for data modeling, transformation design, and BI-ready architecture.
• Expand and enhance current standards as our platform and operational maturity evolve.
• Establish operational standards that align with our long-term platform vision (model governance, review processes, documentation, and change management).

Cross-Functional Collaboration

• Map raw data through movement stages/lifecycle, partnering with data engineering to translate source data into standardized, curated structures fit for analytics consumption.
• Translate business and analytical requirements into scalable, well-modeled data structures.
• Collaborate deeply with stakeholders to gather requirements, define business processes, translate needs into data models, and ensure shared understanding of definitions and outcomes.
• Work cross-functionally across silos, aligning with data engineers, BI developers, and platform teams to ensure consistent definitions, governed datasets, and maintainable solutions.
• Provide coaching and mentorship that builds a culture of colleague development and mutual investment.

Data Transformation Enablement:

• Collaborate on transformation strategy and design to ensure transformations align with dimensional modeling outcomes.
• Support patterns that promote reliability, auditability, and clarity from source to curated BI layers.

Data Quality, Testing, and Reliability

• Ensure data quality and correctness by partnering on testing strategies, reconciliation approaches, and validation rules that confirm models meet business expectations end-to-end.
• Participate in defining checks/controls that ensure trusted data for enterprise reporting and analytics.