Data Platform Architect

Role Overview

• 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.
• 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.
• 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).
• 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.
• 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.
• 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.

Requirements

• 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.

Tech Stack

• Cloud

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 and 2 paid days for volunteer time each calendar year.