The individual will design and scale an enterprise semantic layer to transform raw restaurant data into business-ready insights. This role involves defining and governing canonical key performance indicators while building metadata-driven semantic models for critical business domains. The position requires implementing a hybrid semantic architecture that combines manual models with AI-driven context engineering. The engineer will enable data consumption through business intelligence tools, application programming interfaces, and artificial intelligence applications. Furthermore, the role entails integrating semantic metadata into large language models, agents, and copilots. The professional will also establish governance, validation, versioning, and change management processes while partnering with cross-functional teams to drive adoption.

The role requires a minimum of five years of experience in data engineering, analytics engineering, or artificial intelligence and machine learning systems. Candidates must possess strong proficiency in semantic modeling, SQL, and Python. Experience with DBT and modern cloud platforms is necessary for the position. Additionally, the individual must demonstrate an understanding of APIs, distributed systems, and the integration of vendor systems. The role also requires specific experience in enabling data for artificial intelligence and large language model use cases.