The Walt Disney Company

Full-stack Engineer

• Design prototypes and tools supporting Disney Entertainment & ESPN Technology
• Responsible for researching best approaches and architectures to solve interesting and unique problems facing Disney’s businesses.
• Identify elegant solutions to complex and unique problems

Senior Software Engineer – Platform and Infrastructure

Product Manager

• Define Strategy & Vision: Own the long-term growth and monetization strategy across the customer lifecycle—from acquisition to retention and revenue optimization
• Drive Rapid Execution & Impact: Oversee product roadmaps and delivery, ensuring initiatives drive measurable business and customer impact in a fast-moving, dynamic environment
• Lead & Grow Team: Build, coach, and scale a high-performing team of product managers, fostering a culture of deep consumer and business understanding, experimentation, learning, and results
• Balance Value Creation & Capture: Develop innovative offerings that deliver customer value while driving sustainable revenue growth
• Experimentation & Optimization: Establish a culture of A/B testing, data-driven learning, and rapid iteration across acquisition, conversion, and retention funnels
• Ecosystem Thinking: Navigate complex ecosystems, understanding incentives and trade-offs across customer, business, and partner needs
• Cross-Functional Leadership: Collaborate with other product teams, marketing, engineering, design, data, finance, and business development to align on goals and execute effectively
• Platform Mindset: Deeply understand and influence platform capabilities and technical constraints to scale growth and monetization initiatives globally

Executive Director, Product, Growth & Monetization

• Define and execute the long-term strategy for subscription plans and tiering, and evaluate new monetization opportunities.
• Drive plan portfolio evolution across tiers and plans, including students plans and emerging offerings
• Build differentiated experiences tailored to distinct consumer segments, behaviors, and willingness-to-pay profiles
• Partner with Pricing, Finance, Data Science, and Other Product teams to optimize our offering .
• Translate user insights, market trends, and behavioral data into clear product opportunities and prioritization decisions
• Define success metrics and own experimentation frameworks to evaluate customer and business impact
• Collaborate closely with Engineering, Design, Research, and Analytics teams to deliver high-impact customer experiences at scale
• Balance customer value, revenue outcomes, operational complexity, and platform scalability in product decisions
• Influence executive stakeholders with clear communication, strategic thinking, and data-informed recommendations
• Stay current on industry trends across streaming, subscriptions, creator ecosystems, and digital consumer products.

Principal Product Manager – Monetization

Product Designer

• Support the Apparel Product Design team with concept, design, sketch, prototype (including assisting with art-to-product, sample creation where applicable), deliver and present trend-right consumer centric products that feature market-leading innovation and great price/value for each tier of the value pyramid
• Assist in design presentation deliverables: room set up, product mock-ups, boards and line review decks
• Collaborate with internal and external partners to assist product team with design and approval of all products
• Coordinate product submissions for creative reviews and approvals with design team
• Own maintaining product and market samples for the PD team
• Ensures storage spaces are clean and organized
• Support Product Design team in sorting and filing duplicate samples/submissions for the team members not in the same office
• Assist the design team with PLM system, design development tool
• Own keeping items up to date through the sample and development process
• Monitor competitors, product innovation and market dynamics
• Research Initial seasonal trends by category
• Multi-task and prioritize multiple design projects within timelines
• Adapt to change

Assistant Product Designer – Apparel

Data Engineer

• Architecting high-scale, secure and interoperable data platforms across the enterprise to enable AI and analytics applications
• Architecting data domains and designing data products to be shared across the enterprise
• Architecting cross-segment semantic layer and data catalog solutions
• Designing an agentic architecture for exposing data from enterprise data lakehouse domains to AI applications
• Developing MDM strategy and architecting MDM solutions for complex enterprise domains (e.g., Finance, HR)

Lead Data Architect

Operations

• Managing team members and vendors to deliver 24x7 platform technical support, ensuring accurate and timely delivery of critical business data
• Operating high-performance, highly scalable and flexible, cost-effective data integration platform solutions that meet business requirements and conform to architectural designs and technology strategies.
• Overseeing all operational aspects of all platforms and services in the Data portfolio including availability, performance, capacity, currency, scalability, resiliency, security, compliance and licensing
• Responsible for incident management for any outages or incidents impacting live production systems.
• Managing, communications and orchestrating troubleshooting and remediation activities.
• Providing quality and timely resolution of platform defects/ problems & enhancement requests through the management of the application development lifecycle
• Responsible for managing security and compliance for all applications and services in the portfolio
• Running an agile-based request management workflow, focused on maximizing velocity, improving quality and reducing backlog
• Partnering with Business & Solution Architects to identify opportunities for improved customer service, increased agility and availability
• Working with multiple vendor/partners to deliver existing services against Key Performance Indicators, managing performance against contractual terms and identifying new / rationalizing existing services.
• Ensuring Service Operations, Knowledge Management, Continuous Improvement, Service Level & Availability Management are operationalized across the team
• Developing and guiding direct reports by providing career path conversations and mentoring, helping them achieve their goals through effective development and training plans

Senior Manager, Data Systems Operations

Engineering Manager

• Lead, mentor, and develop a team of 4-6 Solution and Software Engineers
• Provide coaching, career pathing, and growth plans for each team member
• Drive architecture, design, and implementation within Moveworks
• Oversee Tier 2 engineering support for production Moveworks HR solutions, ensuring high availability and fast incident resolution
• Collaborate with partner teams to maintain data quality, compliance, and platform integrity
• Partner with Product Managers, Designers, and Platform and Solution Architects to define and prioritize user-centric enhancements that provide measurable value
• Champion agile delivery practices (Scrum, Kanban)
• Communicate technical progress, risks, and delivery status clearly to Technology Leadership, Product and business stakeholders

Manager, Software Engineering

Designer

• Serve as fulltime POC for all ESPN Super Bowl LXI studio/set project management efforts
• Oversee scenic execution, and installation across all assigned SBLXI locations
• Manage timelines, budgets, and vendor coordination from concept through final delivery
• Maintain constant communication with Studio Design leadership to evaluate scenic builds and ensure alignment with ESPN standards
• Coordinate site walks, shop visits, bidding processes, and build reviews as required
• Act as on‑the‑ground liaison between internal stakeholders and local fabrication partners

Manager – Special Project, Studio Design & Development

• Lead the design, development, and deployment of data and application integration solution built using Mulesoft for licensing financial systems and AI-powered applications
• Own the full software development lifecycle, including analysis, design, coding, testing, debugging, and documentation
• Collaborate with product, business, and data science teams to define system requirements and deliver intelligent automation and integration
• Apply machine learning and AI techniques to optimize licensing workflows
• Mentor junior or contracted engineers and foster a culture of innovation, inclusion, and technical excellence
• Stay current with emerging technologies in integration, AI, financial systems, and cloud-native development to inform strategic decisions.

Senior Software Engineer

• Work with a team building high-performance, stable, scalable software
• Participate in the code review process by providing feedback on pull requests
• Participate in the on-call rotation, supporting systems and services during production incidents

Senior Product Software Engineer

Platform Engineer

• Leading teams of developers (both Disney Cast Members and external vendors) in major software/data development projects.
• Designing and developing highly scalable, distributed enterprise data platform solutions.
• Design, develop and implement scalable distributed enterprise data platform solutions, focusing on multi-cluster warehousing, data sharing, and optimized storage.
• Write code that establishes and enhances frameworks and design proof of concepts, and review code for correctness, and its impact on software architecture.
• Lead the development of high-performance ETL/ELT pipelines using tools like dbt, Python, Airflow and more to integrate diverse data sources.
• Provide mentorship and direction to more junior software engineers on the team; serve as an advanced resources for other engineers on the team.
• Being the ongoing technical lead for data platform products (post-implementation)—leading engineering support for the production platform, leading ongoing enhancement projects, guiding technical product roadmap
• Partner with Data Science, Analytics, and Product teams to ensure the platform meets evolving business requirements.
• Establish standards for data modeling (Vault, Star Schema), security (RBAC), and data quality frameworks.

Lead Data Platform Engineer

• Lead a technical team through the delivery of major engineering initiatives, providing guidance for major technical projects related to data platforms and solutions.
• Lead project teams while delivering on-time, on-budget and on-scope.
• Lead the innovation, development and improvement of software and data solutions by managing day-to-day development, testing and implementation of technical solutions.
• Product ownership for data platforms—including setting product strategy and defining and managing the product roadmap.
• Partner closely with business stakeholders to deliver data solutions that meet their business needs.
• Excellent communication skills, ability to communicate well to both technical and business audiences.
• Lead a team of individual contributors and provide mentorship and career development beyond day-to-day technical guidance.

• Writing some and reviewing a lot of code and tests.
• Reviewing code and test implementations for best practices and algorithmic complexity.
• Available to support engineers on an On-Call shift, when needed.
• Reading requirements documentation from Product, providing a perspective on feasibility and translating into implementation tasks, and partnering with teams’ leads through execution as needed.
• Exploring, researching, implementing proofs-of-concept, and proposing solutions that will improve Ad Serving systems (reduce cost and overhead, improve maintainability, minimize the time features take to be in production, etc).
• Defining, reviewing, and documenting software and system designs in a high throughput, low latency microservices environment.
• Enhancing systems’ observability with proper metrics, monitors, and alerts.
• Foster open communication during architectural discussions, confidently defending decisions while welcoming feedback.
• Bridge the gap between diverse team requirements and technical capabilities to deliver cohesive, scalable solutions.
• Mentoring and inspiring others in all aspects of professional software development.

Principal Software Engineer – Ad Experiences

Analyst

• Develop and maintain agent schedules that align with forecasted contact volumes, service level goals, and labor regulations
• Manage shift bid processes for the designated bid location, ensuring fairness and transparency
• Oversee BPO schedule fulfillment processes, ensuring partners maintain key schedules with the flexibility required to manage gaps in cadence with business needs
• Partner with BPO vendors across regions to ensure centralized contact distribution and 24/7/365 coverage
• Apply knowledge of various BPO staffing models to optimize scheduling strategies
• Guide and support RTM operations by identifying opportunities for added shrinkage or supplemental coverage
• Drive improvements in schedule efficiency, occupancy, shrinkage compliance, and RTM readiness through proactive planning

Schedule Optimization Analyst

• Build and maintain high‑performance streaming and batch data pipelines that power AI applications
• Implement and extend embedding generation workflows, vector store integrations, and retrieval pipelines supporting semantic search, RAG systems, and AI assistants
• Develop and optimize scalable storage and retrieval patterns, focusing on cost‑efficient architecture and smooth production performance
• Implement AI‑optimized data models and storage patterns that align with broader enterprise architecture and platform requirements
• Integrate pipelines with shared AI platform services (agent frameworks, registries, feature stores), ensuring clean, versioned, and reliable data delivery
• Build reusable ingestion, transformation, and data processing components that streamline adoption across engineering teams
• Embed end‑to‑end observability into data systems, including metrics, structured logging, automated alerts, drift detection, and failure analysis
• Ensure deployed pipelines meet high standards for reliability, recoverability, auditability, and long‑term maintenance
• Drive execution by owning the full development lifecycle: prototyping, implementation, testing, deployment, optimization, and documentation
• Collaborate closely with infrastructure, ML engineering, product, and governance teams to deliver production‑ready AI capabilities
• Lead by example through strong execution, high‑quality code, and proactive problem solving