Sr. Data Architect

Warner Bros. Discovery; Atlanta (GA); On-site; USD 120,000 - 150,000; Full time

Benefits offered by this job

Career defining opportunities

Curated benefits

Tools for personal growth

Job summary

Warner Bros. Discovery is seeking a Sr. Data Architect in Atlanta, GA, to lead the design of the AI Context Layer and manage semantic architecture for data-driven decision making. The candidate will collaborate with senior leadership and technical teams to optimize data frameworks and implement innovative solutions across our vast data landscape.

The ideal candidate will have over 5 years of experience in data architecture and engineering, specifically with expertise in modern cloud platforms like Snowflake and Databricks. Join us to be part of a team that values collaboration, inclusion, and forward-thinking practices.

Qualifications

• 5+ years of experience in data engineering and architecture.
• Proven track record of designing and implementing Canonical Models.
• Experience with advanced data modeling across multiple paradigms.

Responsibilities

• Architect the AI Context Layer to act as a central source of truth.
• Design and deploy semantic abstraction layers via intelligent APIs.
• Partner with engineering and ML teams for operationalizing data pipelines.

Skills

Data modeling

Cloud architecture

Semantic layers

Data engineering

Education

Bachelor’s degree in Computer Science or related field

Tools

Snowflake

Databricks

Microsoft Fabric

Job description

Overview

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 Role

We are expanding our Enterprise Data & Analytics Group by adding a Sr. Data Architect. The ideal candidate will treat data as a strategic and intelligent asset, architecting the framework that empowers our entire organization to make high-stakes, data-driven decisions and powers our next-generation Agentic AI ecosystems. You will co-own the design of the foundational AI Context Layer—from enterprise ontology and sophisticated canonical domain modeling to the building of universal semantic layers. This is a high-visibility role where you will spearhead modernization efforts, partnering with senior leadership, data engineering, and AI/ML teams to transform an optimized data lakehouse into an interconnected, self-reasoning knowledge engine.

Role Accountabilities

Semantic Architecture & AI Context Layer

• Architect the AI Context Layer: Define the 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 like Snowflake Semantic Views, Databricks Unity Catalog/Liquid Clustering, Fabric Semantic Models, or semantic middleware like dbt/Cube) to expose canonical data via intelligent APIs.
• Drive Data Innovation: Bridge the gap between physical big data performance and semantic meaning, ensuring that AI agents can reason through complex, recursive enterprise relationships without hallucinating.

Technical Design & Canonical Engineering

• Build Canonical Data Products: Lead the design and consolidation of foundational data domains (e.g., Studio, Finance, Content Sales, Consumer Products) into unified, cleansed Canonical Models within the Silver/Gold layers, successfully abstraction-matching data from highly heterogeneous source systems.
• Modernize the Medallion Stack: Implement cutting-edge, resilient lakehouse patterns—including stream processing, event-driven pipelines, and 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 ensure context data, feature stores, and vector embeddings are continuously updated and monitored in production.

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, allowing both traditional business analysts (via self-service BI) and AI Agents to query data with identical semantic consistency.
• Ensure Relationship Integrity: Implement reusable data quality and identity resolution frameworks to handle complex object hierarchies (e.g., mappings across households, profiles, and accounts) across the enterprise lakehouse.

Qualifications & Experiences

• Bachelor’s degree in Computer Science, Information Systems, Data Analytics, Information Technology or similar major
• 5+ years of experience in data engineering and data architecture in a dedicated Enterprise or Domain Architect capacity.
• Proven track record of designing, scaling, and implementing Canonical Models and Semantic Layers that sit on top of massive Enterprise Data Lakes/Lakehouses.
• 5+ years of experience with modern cloud data platforms, specifically possessing deep architectural knowledge in at least one of the following: Snowflake (Dynamic Tables, Cortex, Horizon), Databricks (Unity Catalog, Delta Live Tables), or Microsoft Fabric (OneLake, Semantic Models), alongside cloud ecosystems like AWS or Azure.
• Advanced skill in Data Modeling across multiple paradigms: Relational, Dimensional (Kimball), and highly relational/flexible frameworks like Data Vault 2.0 or Graph-native concepts, along with 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 single, 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.

How We Get Things Done

This last bit is probably the most important! Here at WBD, our guiding principles are the core values by which we operate and are central to how we get things done. You can find them at www.wbd.com/guiding-principles/ along with some insights from the team on what they mean and how they show up in their day to day. We hope they resonate with you and look forward to discussing them during your interview.

Championing Inclusion at WBD

Warner Bros. Discovery embraces the opportunity to build a workforce that reflects a wide array of perspectives, backgrounds and experiences. Being an equal opportunity employer means that we take seriously our responsibility to consider qualified candidates on the basis of merit, without regard to race, color, religion, national origin, gender, sexual orientation, gender identity or expression, age, mental or physical disability, and genetic information, marital status, citizenship status, military status, protected veteran status or any other category protected by law.

If you’re a qualified candidate with a disability and you require adjustments or accommodations during the job application and/or recruitment process, please visit our accessibility page for instructions to submit your request.