<p><strong>Lead Data Architect / Senior Data Modeler</strong></p><p><strong>Location:</strong> Onsite in Burbank, CA (4 days/week, Mon–Thu)</p><p><strong>Team:</strong> Studio Technology – Data Services</p><p><br></p><p><strong>About the Role</strong></p><p>The Studio Technology group at Walt Disney Studios empowers filmmakers, analysts, and business partners with scalable, secure, and innovative data solutions. As part of the Data Services team, you will shape how the Studio builds, organizes, and delivers data — from financial systems to marketing analytics to consumer engagement products.</p><p>We are looking for a Lead Data Architect whose primary passion is data modeling and data architecture, not software architecture. This person lives and breathes semantic models, dimensional design, medallion-layer structuring, and data-as-a-product principles. The ideal candidate is doing this work hands-on today and has done it consistently in recent roles — this is their core craft, not an adjacent skill.</p><p><br></p><p><strong>What You’ll Do (Day-to-Day)</strong></p><p>● Partner with business stakeholders and product managers to understand data requirements and translate them into scalable data strategies and architecture.</p><p>● Design and own semantic models, dimensional models, entity definitions, and medallion-layer data structures (Bronze/Silver/Gold).</p><p>● Determine what gets built where and why, ensuring consistent modeling patterns across projects and data domains.</p><p>● Define and implement data-as-a-product approaches, including domain boundaries, ownership models, SLAs, and documentation standards.</p><p>● Work closely with data engineers to guide how assets should be built, structured, and optimized.</p><p>● Establish and maintain data standards, governance practices, naming conventions, and documentation for modeling and architecture.</p><p>● Provide technical leadership on data modeling best practices across teams, including coaching junior members.</p><p>● Evaluate modern data technologies and recommend tools that improve modeling consistency, performance, and quality.</p><p>● Collaborate with analytics, BI, and data science teams to design models that support reporting, ML/AI workloads, and cross-domain analytics.</p>
