Staff Data Architect

Warner Bros. Discovery•Burbank, CA

1d•$146,440 - $271,960

About The Position

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.

Requirements

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
Expert-level command of relational modeling, dimensional (Kimball) design, and building canonical enterprise schemas.
Mastery of complex SQL (including recursive CTEs, analytical window functions, and semi-structured VARIANT parsing) alongside Snowpark (Python).
Clear understanding of how LLM-driven agents utilize structured enterprise data, APIs, and metadata catalogs to execute complex operational workflows.

Responsibilities

Design and implement the Context Layer across the data products.
Create canonical models in the Silver layer, defining enterprise ontologies, and native Semantic Views.
Ensure that autonomous AI agents have a rock-solid, governed framework to accurately query, traverse, and reason against our data.
Architect, build, and scale our Medallion data pipeline (Bronze-to-Silver-to-Gold) using Snowflake Dynamic Tables, Streams, and Tasks for optimized canonical processing.
Build consolidated, clean entity tables (e.g., Unified Customer Identity, Orders) in the Silver layer from completely mismatched raw source data schemas.
Design native Snowflake Semantic Views to establish the authoritative business definitions of entities, dimensions, facts, metrics, and relationships directly inside the warehouse.
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.
Build PoCs to show lightweight ontology tracking and entity-relationship traversing within Snowflake using advanced SQL techniques.
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.
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.
Perform exploratory and quantitative analytics, data mining, and discovery.
Ensure data security and privacy through appropriate access controls and encryption.
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.
Work 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.