Staff Data Architect

Welcome to Warner Bros. Discovery… the stuff dreams are made of. Who We Are… When we say, “the stuff dreams are made of,” we’re not just referring to the world of wizards, dragons and superheroes, or even to the wonders of Planet Earth. Behind WBD’s vast portfolio of iconic content and beloved brands, are the storytellers bringing our characters to life, the creators bringing them to your living rooms and the dreamers creating what’s next… From brilliant creatives, to technology trailblazers, across the globe, WBD offers career defining opportunities, thoughtfully curated benefits, and the tools to explore and grow into your best selves. Here you are supported, here you are celebrated, here you can thrive. Your New Role : We are expanding our Enterprise Data & Analytics Group by adding a Staff Data Architect professional that will be a data-driven leader with deep experience designing robust enterprise data architectures that support business objectives. This role will help advance the company’s modernization efforts on cloud data platform, enabling a next-generation enterprise AI ecosystem that moves beyond basic chat interfaces and analytics workloads to support Agentic AI systems capable of autonomous reasoning. To achieve this, the Staff Data Architect will work on bridging the gap between massive physical data layers and semantic business context. Staff Data Architect works closely with research, engineering, product management and other developers to design, build, and deploy data warehouse solutions and reporting tools that meet the growing AI and analytical needs of our organization. Your Role Accountabilities: As a Data & Semantic Architect, you will design and implement the Context Layer across the data products. You will be responsible for creating canonical models in the Silver layer, defining enterprise ontologies, and native Semantic Views. Your work will ensure that autonomous AI agents have a rock-solid, governed framework to accurately query, traverse, and reason against our data. Data and Semantic Architecture : Snowflake Lakehouse Architecture: Architect, build, and scale our Medallion data pipeline (Bronze-to-Silver-to-Gold) using Snowflake Dynamic Tables , Streams, and Tasks for optimized canonical processing. Canonical Modeling & Semantic Mapping: Build consolidated, clean entity tables (e.g., Unified Customer Identity, Orders) in the Silver layer from completely mismatched raw source data schemas. Snowflake Semantic Views Design: Design native Snowflake Semantic Views to establish the authoritative business definitions of entities, dimensions, facts, metrics, and relationships directly inside the warehouse. AI Grounding with Cortex: Configure and tune Snowflake Cortex Analyst and Cortex Search by provisioning clean semantic models and relationship metadata, ensuring AI agents can achieve high accuracy on natural language queries without hallucinations. Ontology & Graph-Native Modeling in SQL: Build PoCs to show lightweight ontology tracking and entity-relationship traversing within Snowflake using advanced SQL techniques Data Governance & Contracts: Leverage Snowflake Horizon capabilities to enforce column/row-level security, data quality guardrails, and version-controlled metric schemas so that updates to the semantic plane do not break downstream AI workflows. Data Strategy & Governance : Collaborate with stakeholders to define data strategies and roadmaps. Establish and maintain data governance frameworks to ensure data quality and compliance. Implement re-usable data quality frameworks. Stay up to date with the latest cloud data technologies and trends. Evaluate and recommend new data technologies and tools. Come up with best practices, well architected guidance to improve the quality, performance and scalability of the solutions built on Snowflake platform Change how we think, act, and utilize our data by performing exploratory and quantitative analytics, data mining, and discovery. Ensure data security and privacy through appropriate access controls and encryption. Data Integration & Management: Design ETL/ELT processes for data integration from various sources. Build software across our data platform, including event driven data processing, storage, and serving through scalable and highly available APIs, with awesome cutting-edge technologies. Optimize data storage and retrieval for efficient data access. Collaboration & Communication: Help us stay ahead of the curve by working closely with data engineers, stream processing specialists, API developers, our DevOps team, and analysts to design systems which can scale elastically. Work closely with business analysts & business users to understand data requirements. Provide technical leadership and mentorship to junior team members. Help build and maintain foundational data products such as but not limited to Finance, Titles, Content Sales, Theatrical, Consumer Products etc. Collaborate with data engineering, data platform, and data strategy teams to achieve organizational objectives. Qualifications & Experiences: Bachelor's degree in computer science, information systems, or information technology or similar major 8+ years of enterprise data architecture experience with a proven track record of deploying large-scale Snowflake ecosystems with a focus on Domain Modeling, AI Orchestration, & Semantic Governance. Minimum 3 years of experience with advanced, hands-on architectural experience with Snowflake in enterprise data space is highly preferred. Experience in the competent tech stack is also preferred. Proven experience or deep working knowledge of Snowflake Semantic Views , Cortex AI (Analyst/Search) , Snowflake Horizon , and Dynamic Tables Data Modeling: Expert-level command of relational modeling, dimensional (Kimball) design, and building canonical enterprise schemas. Advanced SQL & Processing: Mastery of complex SQL (includi