Jobs at The Walt Disney Company

Lead an Apple platform engineering team building foundational components for Disney+ and Hulu across iPhone, iPad, Apple TV, and Apple Vision Pro. Own technical direction, code quality, team execution, OKR alignment, cross-discipline collaboration with Product/Design/QA, career development, and project delivery while driving platform standards and process improvements.

Design, build, and maintain high-performance, scalable backend services and data pipelines for streaming media. Participate in code reviews, on-call rotations, and mentor junior engineers. Collaborate with data teams to ensure observability, reliability, and alignment between architecture and implementation.

Design, build, and maintain scalable, secure web identity experiences (login, registration, account and profile flows). Collaborate with product, design, and backend teams, lead delivery of complex features, write well-tested maintainable code, mentor teammates, troubleshoot production issues, and improve architecture, tooling, and lifecycle operations for large-scale identity systems.

As a Software Engineer II, you will develop and maintain software components, collaborate with teams, and ensure code quality while supporting business operations at Disney.

Design, build, deploy, and operate scalable cloud data pipelines and warehouse solutions to provide trusted security data. Lead platform architecture, implement IaC and DevOps practices, enforce engineering best practices, and partner cross-functionally to deliver data capabilities supporting security initiatives.

Lead and grow a team of Data Product Managers to define, build, and deliver domain-driven data products. Align data product strategy with business goals, provide architectural guidance for Snowflake/dbt/AWS-based pipelines, and ensure data readiness for AI/ML. Drive operational excellence, governance, vendor management, and cross-functional collaboration to enable scalable, secure, and high-quality data products.

Lead and grow a multidisciplinary software and data engineering team building data pipelines, AI-enabled analytics, and custom BI dashboards. Own roadmaps, delivery, SDLC practices, data governance, and cross-functional collaboration with product, program, QA, and BI partners to ensure scalable, reliable analytics platforms and polished UI components.

Lead enterprise data governance for Disney's Data Unification initiative: define and enforce policies, embed governance in semantic models and federated platforms, ensure security/privacy/compliance, implement metadata/lineage/quality strategies, support semantic data products and AI governance, and drive adoption and reporting.

Lead design, development, and governance of enterprise ontologies, semantic layers, and knowledge/ entity graphs. Implement graph and vector databases, enable LLM-augmented search and federated data access across Snowflake, Databricks, PostgreSQL, MongoDB, S3, and Kafka. Drive data cataloging, security models, ontology governance, and mentor teams to translate business goals into ontological solutions.

Design, build, and maintain scalable, fault-tolerant identity and device data pipelines and backend systems. Modernize data models, improve code quality and test coverage, support production operations and on-call, collaborate with product and cross-functional teams, and participate in code reviews and agile ceremonies.

Lead development teams in creating scalable data platforms, focus on ETL/ELT pipelines, data architectures, mentoring junior engineers, and ensuring project alignment with business goals.

Lead architecture, development, administration, and automation for Atlassian Cloud B2B products (Jira/Confluence). Build Forge apps, manage plugins/integrations, troubleshoot escalations, gather and optimize requirements, document configurations, and support deployments and upgrades across cloud/on‑prem/AWS environments while partnering with stakeholders and vendors.

Lead technical teams to deliver large-scale data platform initiatives (data lakehouse) as product owner and delivery manager. Own product strategy and roadmap, partner with business stakeholders (Finance/HR), manage development, testing, implementation, and mentor engineers while ensuring on-time, on-budget delivery of enterprise analytics, BI, EPM and AI/ML data solutions.

Design, build, and maintain Identity Householding data products and scalable batch/real-time pipelines. Improve data models and code quality, increase test coverage, collaborate with product and engineering teams, participate in on-call support, code reviews, and CI/CD-driven deployments using Databricks, Spark, cloud databases, Airflow, and AWS S3.

Build and maintain performant, accessible front-end features and reusable UI components using React and TypeScript. Collaborate with backend, product, and QA to deliver pixel-perfect implementations, unit tests, and production issue resolution. Advocate for quality, optimize performance, and work within Agile teams to meet project deliverables.

As a Software Engineer II, you'll enhance observability solutions, build data pipelines, improve system monitoring, and collaborate on technical designs and code quality.

Develop and maintain Disney+ client applications for iOS, tvOS, and visionOS using Swift. Build complex user interfaces with UIKit/SwiftUI, write unit and integration tests, participate in code reviews, collaborate with product and design teams, and specialize in Apple platform technologies to deliver high-quality streaming experiences.

Lead and deliver HR-focused enterprise application projects end-to-end. Define scope, manage schedules, risks, finances, and stakeholders; produce status reporting and visualizations; support Agile/Waterfall models and PMO standards using tools like Smartsheet, Clarity, Jira, and MS Office.

Lead end-to-end product lifecycle for data governance products: set strategy, roadmaps, requirements, and success metrics; drive cross-functional delivery, integrations, and technical decisions; use research and KPIs to prioritize; improve reliability and usability; and communicate outcomes to stakeholders.

Lead development and productionization of personalization and recommendation algorithms (ranking, retrieval, content/user understanding, post-ranking). Apply modern AI/LLM techniques, design and run offline and online experiments, drive technical vision and roadmap, collaborate with engineering/product/data teams, and build maintainable, production-grade ML systems at scale.