Sr. Data Architect

Role Overview We are expanding our Enterprise Data & Analytics Group by adding a Sr. Data Architect. The ideal candidate treats data as a strategic and intelligent asset, architecting the framework that empowers our organization to make high‑stakes, data‑driven decisions and powers next‑generation Agentic AI ecosystems. Accountabilities Semantic Architecture & AI Context Layer Architect the AI Context Layer: Define vision, requirements, and roadmap for an Enterprise Ontology and Semantic Layer that acts as the 'world map' and central source of truth for Agentic AI, LLM prompting, and GraphRAG systems. Build the Semantic Layer: Design and deploy semantic abstraction layers using native platform capabilities (Snowflake Semantic Views, Databricks Unity Catalog/Liquid Clustering, Fabric Semantic Models) or semantic middleware (dbt/Cube) to expose canonical data via intelligent APIs. Drive Data Innovation: Bridge the gap between physical big data performance and semantic meaning, ensuring AI agents can reason through complex, recursive enterprise relationships without hallucinating. Technical Design & Canonical Engineering Build Canonical Data Products: Lead design and consolidation of foundational data domains into unified, cleansed Canonical Models within the Silver/Gold layers, abstracting data from heterogeneous source systems. Modernize the Medallion Stack: Implement resilient lakehouse patterns—stream processing, event‑driven pipelines, schema‑on‑read ingestion—to feed the canonical layers seamlessly. Operationalize AI Context Pipelines: Partner with ML/DevOps teams to architect and maintain MLOps and LLMOps processes that keep context data, feature stores, and vector embeddings continuously updated and monitored. Governance, Quality & Semantic Integrity Standardize & Automate Contracts: Develop and enforce enterprise‑wide standards for metadata management, data contracts, and semantic version control through automated frameworks and CI/CD integration. Enable AI & Data Democracy: Ensure data and its underlying business logic are highly discoverable and machine‑readable, letting analysts and AI Agents query data with identical semantic consistency. Ensure Relationship Integrity: Implement reusable data quality and identity resolution frameworks to manage complex object hierarchies across the enterprise lakehouse. Qualifications & Experiences Bachelor’s degree in Computer Science, Information Systems, Data Analytics, Information Technology or related field. 5+ years of experience in data engineering and data architecture in a dedicated Enterprise or Domain Architect capacity. Proven track record designing, scaling, and implementing Canonical Models and Semantic Layers atop large Enterprise Data Lakes/Lakehouses. 5+ years of experience with modern cloud data platforms, with deep architectural knowledge of at least one of: Snowflake (Dynamic Tables, Cortex, Horizon), Databricks (Unity Catalog, Delta Live Tables), or Microsoft Fabric (OneLake, Semantic Models), plus AWS or Azure ecosystems. Advanced data modeling skills across Relational, Dimensional (Kimball), and flexible frameworks such as Data Vault 2.0 or Graph‑native concepts, and proficiency in enterprise modeling tools. Demonstrated ability to build, maintain, and version‑control an ontology or semantic map (e.g., translating messy source attributes into a unified business entity layer). Solid understanding of FinOps—managing and optimizing cloud compute/storage consumption to maintain platform ROI while running complex semantic or AI workloads. Equal Employment Opportunity Warner Bros. Discovery is an equal‑opportunity employer. We consider qualified candidates on the basis of merit without regard to race, color, religion, national origin, gender, sexual orientation, gender identity, age, mental or physical disability, marital status, citizenship status, military status, protected veteran status or any other legally protected category. If you are a qualified candidate with a disability and require accommodations during the application or recruitment process, please visit our accessibility page for instructions to submit your request. #J-18808-Ljbffr