The Walt Disney Company

Director

• Lead strategic preparation for major media rights renewals by organizing historical agreements, evaluating contractual obligations, identifying business opportunities, and coordinating enterprise-wide negotiation readiness.
• Lead and support negotiations for high-profile sports rights agreements, renewals, amendments, and strategic partnerships.
• Partner closely with senior Programming, Legal, Distribution, Ad Sales, Direct-to-Consumer, and Business Development leaders to maximize the value and flexibility of acquired rights.
• Evaluate new rights opportunities and emerging market trends, developing recommendations that support ESPN and TWDC's broader content strategy.
• Serve as a trusted advisor during complex negotiations, balancing business objectives, contractual protections, and partner relationships.
• Act as the central point of contact for league partners and rights holders on all business affairs matters.
• Provide strategic guidance and risk assessment on contractual issues, identifying solutions that align with both business priorities and legal requirements.
• Collaborate with executive leadership to develop scalable processes, governance structures, and best practices that support business growth and operational efficiency.
• Ensure alignment between contractual obligations and evolving distribution, monetization, and content strategies across the enterprise.
• Lead the Content Rights Management function, ensuring accurate interpretation, documentation, and administration of contractual rights across multiple platforms and businesses.
• Oversee the creation and maintenance of rights summaries, contract analyses, reporting frameworks, and compliance processes.
• Establish and maintain enterprise-wide standards, systems, and procedures that ensure contractual obligations are fulfilled, rights are fully leveraged, and cross-functional business initiatives remain compliant across ESPN and TWDC.
• Partner with Programming leadership, including senior executives responsible for content strategy, to support long-term content planning and rights portfolio management.
• Build strong internal alignment around key rights decisions and associated business implications.
• Lead, develop, and mentor a high-performing team of business affairs and rights management professionals.

Senior Director, Programming Business Affairs

Business Analyst

• Work with the CORE manager to craft multiple executive-facing reports covering the entire body of technical work
• Maintain excellent, effective relationships with leaders and contributors
• Assess opportunities for additional reporting harmonies and new ways of working
• Act as steward for our technology roadmap
• Collaborate with program, product, operations, and engineering teams
• Distill insights, synthesize, and craft compelling messaging for executive audiences

Full-stack Engineer

• Design and deliver agentic analytics experiences: natural-language and AI-assisted dashboard authoring, agent-accessible surfaces, and AI-generated insights with human-in-the-loop review.
• Lead projects end to end: partner with product, design, and data teams to scope ambiguous problems and distill requirements into clear design and technical specifications.
• Build the full path: a responsive React front end, the Node.js (and Python or Java) services behind it, and the APIs and data-integration layer that feed it.
• Engineer for dashboard-shaped traffic across client and server: optimize data fetching, caching, request batching, and progressive and streaming rendering so complex, high-cardinality views load fast and scale to a large concurrent audience.
• Write, maintain, standardize, and enforce code quality through testing (including test-driven development where it fits), code review, observability, and accessible, resilient UI.
• Mentor engineers at all levels, including senior engineers, through code review, pairing, and knowledge sharing.

Lead Product Software Engineer

Platform Engineer

• Write and Maintain Software Solutions : Design, write, test, and deploy high-quality code to develop reliable, maintainable software solutions.
• Collaborate with Cross-Functional Teams : Work closely with platform engineers, product teams, and data scientists to ensure technical solutions effectively support business goals and content strategies.
• Production Support : Monitor and optimize production systems, ensuring platform stability, performance, and uptime.
• Mentorship: Provide technical guidance and mentorship to junior engineers, fostering a culture of collaboration and continuous learning.

Senior Software Engineer – Content Platform Engineering

Data Engineer

• Design, implement, and oversee the enterprise data governance strategy
• Work in close partnership with the Ontology/Semantic Librarian and Data Engineering teams
• Lead the development and enforcement of data governance policies, standards, and best practices
• Collaborate with Data Engineering teams to implement governance in federated querying, GraphQL interfaces, vector databases, and RAG pipelines
• Define and maintain enterprise data stewardship processes
• Establish governance frameworks for data security, privacy, and compliance
• Design and implement data quality, metadata, and lineage strategies
• Contribute to the internal Data Marketplace by defining governance requirements for semantic data products
• Drive data governance training, change management, and adoption across business, engineering, and AI teams
• Monitor and report on governance metrics, risks, and compliance posture for the Data Unification program

Lead Data Engineer – Governance

• Lead the design, development, and governance of enterprise ontologies, semantic layers, and knowledge graphs.
• Combine deep semantic modeling expertise with hands-on implementation of graph technologies, vector databases, and federated data architectures.
• Design and build enterprise ontologies and semantic models that align business objectives with technical implementation.
• Lead the creation and maintenance of semantic layer graphs, knowledge graphs, and entity graphs.
• Develop and implement strategies for using vector databases and graph databases to enable powerful LLM-augmented search and reasoning.
• Partner with data engineering, AI, and business teams to translate business goals into ontological models.
• Contribute to the development of a unified data access layer that supports querying across diverse data sources.
• Implement and enforce enterprise security models through the ontology and semantic layer.
• Collaborate on AI integration initiatives, including building ontology-driven agents.
• Establish ontology governance processes and contribute to the internal Data Marketplace.

Lead Data and Ontology Engineer

Operations

• Work with a small but dynamic team responsible for monitoring and troubleshooting the VOD ingestion pipeline
• Subject matter and technical expert for supply chain operations
• Review audio/visual content against strict deadlines
• Coordinate with external partners to fix content to ensure deadlines are met
• Research and normalize metadata
• Create tracking tickets for assets that need remediation and follow them to completion
• Provide technical expertise for content issues with A/V, XML, and timed text
• Monitor the health of the encoding pipeline and provide technical and operational support
• Identify and triage internal incidents, escalating them to the appropriate technical teams in a timely manner
• Update documentation and train team members on procedures
• Provide ongoing status of the overall health of the ingest pipeline to senior staff

Media Delivery Ops Specialist

• The Software Engineer is responsible for developing high-quality software solutions that support business needs and align with enterprise technology standards.
• Participate in the development and delivery of complex CMS websites, integration, and services for our internal partners, from initial discovery through launch, ongoing iteration, and operations.
• Design, develop, test, and deploy software solutions that align with functional specifications and technical standards.
• Write clean, maintainable, and secure code with attention to performance and reusability.
• Translate business requirements and user stories into technical tasks and working features.
• Collaborate with senior engineers to refine solution designs and learn architectural best practices.
• Integrate systems using REST APIs, message queues, or platform-specific tooling.
• Participate in code reviews and incorporate feedback to continuously improve code quality.
• Apply established engineering patterns and architectural standards in day-to-day development work.
• Build knowledge of enterprise frameworks and principles of scalable system design.
• Support QA and release processes by writing test cases, fixing bugs, and participating in deployment reviews.

Software Engineer II

Solutions Engineer

• Support the execution and maintenance of an annual and long-term strategic plan for streaming’s revenue growth, ensuring revenue tracking accuracy
• Assist the Sr. Manager in facilitating collaboration across teams to identify innovative and market-leading ad sales opportunities tied to Hulu and Disney+ content, audience insights, and ad product capabilities
• Assist the Sr. Manager in collaborating with internal partners such as RYM, Analytics and Addressable Sales to optimize available streaming opportunities in the marketplace and develop net new approaches to driving streaming revenue
• Support our approach of Streaming growth holistically by building relationships and solutions with our internal content and solutions partners (Entertainment, Sports)
• Under guidance of the Sr. Manager, identify opportunities for optimization, recommend processes to streamline, and maintain internal processes to promote cross-functional collaboration, operational efficiency, and revenue tracking
• Create timely materials to push relevant opportunities in the market for the Sales team to drive revenue

Associate Manager, Streaming Solutions

Data Scientist

• Own the product vision, strategy, and roadmap for data integration, analytics, and AI capabilities supporting vendor management optimization and cost transparency.
• Drive outcome based prioritization across initiatives (e.g., cost transparency, spend visibility, performance insights, workflow automation), balancing stakeholder needs, feasibility, and measurable impact.
• Translate business and operational needs into epics, user stories, acceptance criteria, and a prioritized backlog, partnering with delivery teams through refinement and release planning.
• Define and deliver product capabilities that enable vendor performance visibility, portfolio insights, and spend transparency, including clear success criteria and user outcomes.
• Define data requirements and integration needs, enabling reliable, analytics ready views across systems to support planning, forecasting, and performance tracking.
• Support delivery of AI ‑ assisted capabilities (e.g., forecasting, anomaly detection, insight summarization) within established platforms, standards, and guardrails.
• Lead ongoing backlog management, UAT, and release readiness, accountable for adoption and delivery of measurable business outcomes.
• Communicate product plans, trade-offs, risks, and insights clearly to business and technical stakeholders.
• Facilitate alignment across cross-functional partners with differing priorities through structured discussions and clear decision framing.
• Support governance, controls, and compliance requirements related to data, financial transparency, and operational processes.
• Help drive adoption of new product capabilities and workflows through clear documentation, enablement, and change support.
• Contribute to risk mitigation and continuous improvement through standards, transparency, KPI tracking, and post-implementation review.

Lead Product Manager, Data & AI Integration

Machine Learning Engineer

• Ideate, develop, iterate on, and productionize personalization algorithms, including core ranking, content and user understanding models and graphs, candidate retrieval, and post-ranking systems.
• Apply modern AI and LLM techniques to recommendation systems.
• Contribute ideas and insight on recommendation approaches, evaluation methodology, and how we define data, features, and objectives for our models.
• Help drive the technical vision and innovation agenda for personalization.
• Design and run rigorous offline and online experiments, and contribute to improving our evaluation systems and methodology.
• Work closely within the team and across Engineering, Product, and Data partners, communicating methodologies clearly to technical and non-technical audiences.

Lead Machine Learning Engineer

Product Designer

• Set team values and manage individuals at different stages of development
• Own the vision for your group, its relationship with the department and business goals, and provide clarity when it's needed
• Help your ICs work more effectively and encourage them to implement the most desirable design solution
• Develop, codify, and evangelize best practices, primarily focusing on design excellence, team growth, and stakeholder management
• Guide your team to develop processes for ensuring a high bar of quality, including evolving critique practices, design rituals, and workflows that keep pace with emerging tools and technologies
• Set the strategy and vision for your area of ownership, even as the boundaries of that area shift
• Offer a strong product and design voice with your cross-functional partners
• Partner closely with product management, engineering, research, and data science as a true strategic peer
• Co-author product strategy and champion the user perspective in roadmap conversations
• Stay close to users through research and experimentation, helping define how people discover, interact with, and experience content across current and future paradigms
• Foster a culture of confidence, accountability, design thinking, continuous learning, and constructive critique
• Recruit new designers and actively participate in the hiring process, raising the bar for talent while building a team that reflects diverse perspectives and backgrounds

Manager, Product Design

• Contribute to maintaining, updating, and expanding existing AI intelligence layer encompassing Snowflake Cortex, AWS Bedrock
• Architect, design, and code shared libraries that abstract complex business logic
• Collaborate with product managers, architects, and other engineers
• Contribute to developing and documenting both internal and external standards and best practices
• Ensure high operational efficiency and quality of the AI projects
• Engage with and understand our customers
• Maintain detailed documentation of your work

Lead Product Software Engineer – Data Foundation Platform

• Design, craft and own high quality foundational datasets to produce reliable, meaningful inputs for machine learning models and subscriber experiences
• Source, analyze and validate diverse upstream data sources from upstream partner teams and raw signals using exploratory data analysis
• Identify and build new user and content data features for recommendation systems through collaboration with machine learning engineers
• Enhance existing feature quality through experimentation, analysis and iterative development
• Build, optimize and maintain large scale data processing jobs, pipelines and workloads
• Improve data quality and reliability through implementing checks, anomaly detection, testing, monitoring and alerting
• Contribute to operational excellence by following observability best practices and participating in an on-call rotation to support critical production data pipelines

Data Engineer II

• Define and own the strategic vision and roadmap for data products across multiple business domains.
• Translate high-level business problems into technically grounded data product requirements rooted in consumption-ready data architectures, Kimball-inspired dimensional modeling concepts, and Domain-Driven Design (DDD) bounded contexts.
• Align roadmap priorities with overall company objectives and communicate strategic direction to stakeholders at all levels.
• Lead requirements discovery and translate business needs into precise, engineer-ready specifications.
• Author acceptance criteria that bridge business intent and technical implementation.
• Partner directly with Data Product Engineers and Data Architects to bridge business intent and technical execution.
• Collaborate with AI/ML and data science teams to define data product requirements that support machine learning initiatives.
• Define and enforce data governance standards, metadata management practices, data lineage tracking, and data observability frameworks across the data product portfolio.
• Partner with Data Governance and Architecture teams to ensure all data products meet quality, security, and compliance requirements.
• Define KPIs and success metrics, monitor product performance, and use feedback to guide continuous iteration.