The Walt Disney Company

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

Engineering Manager

• 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.

Full-stack Engineer

• 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

Data Engineer

• 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

Senior Data Engineer

Machine Learning Engineer

• Lead, mentor and guide Data Scientists, Machine Learning and AI engineers to build solutions adhering to industry best practices and deliver scalable solutions including model architecture and algorithm selection
• Lead by example and always strive to improve the design for more scalable, cleaner, and decoupled implementations
• Drive adoption of best practices in model development, code quality, testing, and documentation
• Solid understanding and usage of automated tools (AI) while adhering to company policy
• Define strategic direction for machine learning projects and collaborate with product and engineering stakeholders
• Oversee end-2-end machine learning workflow, including data collection, model development, deployment and modeling
• Foster innovation by exploring new ML techniques, tools, and technologies
• Communicate strategies, progress, and results to leadership and cross-functional teams
• Ensure responsible AI practices, including fairness, explainability, and compliance with privacy and ethical standards
• Develop partnerships across the organization to identify and prioritize high-impact ML opportunities
• Available for On-Call rotations based on the team’s escalation policy and support schedule for ML/AI solutions

Manager, Machine Learning Engineering – Ad Platforms

Auditor

• Actively lead and participate in regularly occurring Operational Safety audits throughout the Disney Experiences segment throughout the various stages of the audit (e.g., scope development, audit activity, post-audit follow up, etc.)
• Leverage data driven information, documented procedure and in-field observations to verify safety critical operating practices align with both Disney and External safety standard.
• Develop expertise in attractions, transportation, entertainment, recreation and other operations focused lines of businesses to effectively understand operating practices to audit against.
• Build relationships with leaders at all levels to gain their trust and assure the audit findings, observations, and understandings developed are accurate to the operations in review.
• Drive stakeholder agreement on any items from the audit processes to help develop actionable plans for mitigation.
• Create and present Management and Executive audit report-outs that include driving follow-up requirements to completion.
• Act as a regular representative for operations related initiatives through reoccurring meetings with partners throughout the segment.
• Steer technical conversations with Senior Leadership with a confident/fact-based approach to drive actionable conclusions to identified issues.
• Proactively drive both short-term and long-term scope planning, using subject matter expertise to make decisions to influence audit decisions for all audit activity for the team.
• Champion one or multiple operations lines of businesses supported by WSA, by working directly with WSA Leadership and Operations leadership to serve as a resource for answers and decision making as events occur.
• Use auditing expertise to diagnose the root cause behind any systemic issue found, both in regular auditing and through other investigation work.
• Act as a mentor to team members and clients by daily actions, direction provided, and thoughtfulness when making critical decisions.

Senior Safety Auditor

• Design, develop, and maintain backend services using Java and JVM‑based technologies
• Contribute production‑quality code with a focus on scalability, performance, security, and reliability
• Collaborate with senior engineers to evolve service architecture, APIs, and data models
• Participate in code reviews, testing, and operational readiness to ensure high code quality
• Work within a modern DevOps environment, contributing to CI/CD pipelines, monitoring, and operational support
• Help deliver features iteratively, incorporating feedback and continuously improving the platform
• Learn and apply new technologies, including AI‑enabled capabilities, as they relate to media servicing workflows

Product Software Engineer II

People Operations

• Translate complex business questions into structured research and analytical approaches.
• Design and execute research initiatives leveraging behavioral science principles.
• Analyze large, complex datasets to identify patterns, trends, and actionable insights.
• Develop and standardize front-end research processes, ensuring consistency and scalability.
• Implement and maintain data governance and quality control standards across projects.
• Build dashboards, visualizations, and storytelling outputs to communicate insights effectively.
• Collaborate with cross-functional partners to align insights with business priorities.
• Stay current on emerging technologies and quickly adopt new tools to enhance analytics capabilities.

Senior Analyst, People Research

• Designing, implementing, and testing solutions to various engineering problems in a high-throughput, low-latency microservices environment.
• Enhancing systems’ observability with proper metrics, monitors, and alerts.
• Reading and understanding product user stories, and then translating them into actionable tasks, including identifying where AI/ML-driven solutions may be applicable.
• Taking ownership of one or more of the team's domain areas.
• Understanding and using automated tools (AI) while adhering to company policy.
• Available for On-Call rotations based on the team’s escalation policy and support schedule.
• Design and integrate AI/ML-supported functionality when appropriate, such as LLM-assisted processing or model-driven decisioning.
• Develop and refine prompts and evaluation of workflows when working with LLM-based APIs.
• Adding evaluation/observability for LLM workloads (telemetry, traces, guardrails).
• Building agentic workflows (multi-step, tool-using agents) and supporting multi-agent orchestration patterns (MCP, agent-to-agent).
• Collaborate with data science and ML platform teams to operationalize models and embed ML-driven features.

Senior Product Software Engineer – Ad Decisioning Engineering

• Develop, enhance, and maintain well-scoped software components and services with attention to code quality, reliability, performance, and security.
• Apply standard engineering practices across design, implementation, testing, debugging, and deployment, with guidance from senior engineers as needed.
• Use organization-approved development tools and practices—including, where appropriate, AI-assisted engineering tools—to accelerate delivery while maintaining full accountability for the correctness, security, and maintainability of committed code.
• Critically review proposed changes (including AI-generated or AI-assisted suggestions) for fit with established patterns, edge cases, security implications, and operational impact prior to merge and release.
• Collaborate with peers and cross-functional partners (for example, Product Management and Quality Assurance) to clarify requirements, constraints, and acceptance criteria, and to deliver aligned solutions.

Software Engineer II

• Deliver software projects with high quality on time
• Provide domain expertise and innovative solutions to complex business problems
• Collaborate with leads and contribute to software architectures which are robust, scalable, fault-tolerant, secured and cloud-native
• Possess Salesforce CRM Analytics solution design and implementation experience
• Reason logically and creatively, identifying problems, drawing valid conclusions from the data available, and develop effective solutions
• Stay up-to-date on the latest software development technologies and trends
• Contribute to code reviews and ensure that all code meets quality standards
• Deliver multiple projects utilizing an Agile methodology
• Take a high ownership, self-sufficient, hands-on position on the team to contribute and drive quality
• Write complex programs, analyze code changes and suggest improvements
• Investigate and resolve any production issues from end user (UI) to persistence layer
• Work with the team to make sure all project deliverables are on time and high quality
• Work collaboratively with cross-functional teams to ensure that software solutions align with business goals

Software Engineer II – Ad Platform, Salesforce CRM Analytics

Director

• Supports the VP, Production & Planning in strategically planning feature films and other projects
• Manages Studio’s production plan templates for features, specials, and shorts projects
• Creates initial production plans and resource schedules
• Collaborates with Finance to translate early show plans into budgets
• Provides recommendations on how to optimize studio resources
• Responsible for data from past projects to generate dashboards, reports, and presentations
• Partners with Production leadership to create consistent production milestones
• Manages a team that owns and supports the production tracking tool

Director – Production, Planning

• Develop and keep relevant a vision for team in a fast-paced, complex and evolving arena.
• Foster a high-performing team of AI/ML engineers and drive a culture of excellence.
• Define and execute a comprehensive MLOps roadmap.
• Manage a high-performing team in a matrixed environment.
• Design, build, and champion a library of reusable building blocks for scientists and modelers.
• Champion the adoption of a portfolio-wide metrics process to increase visibility of KPIs.

Director, Decision Science AI/ML Engineering – Ops

Security Engineer

• Transform GRC at Disney
• Drive continuous evolution of Disney’s InfoSec GRC program, replacing compliance-centric, checkbox-driven operations with a dynamic, risk-intelligence-led model that directly informs how Disney prioritizes investment, staffing, and remediation.
• Define what “great” looks like, not by referencing existing standards but by advancing them.
• Develop novel approaches to risk quantification, compliance automation, and governance integration.
• Partner with GIS Leadership and Segment CTO teams to ensure the GRC program functions as a strategic business enabler, translating complex risk landscapes into executive- and board-ready insights that drive confident decision-making.
• Champion a culture shift across all of GIS and the broader enterprise: risk awareness is everyone’s job, and GRC’s role is to make risk-informed thinking intuitive, not burdensome.
• Oversee the development and ongoing operations of Disney’s comprehensive InfoSec Risk Management program, including the establishment, implementation, and continuous improvement of the enterprise Risk Management Framework.
• Establish and operationalize risk tolerance frameworks in partnership with executive leadership, defining clear thresholds that translate business appetite into actionable security investment and prioritization decisions.
• Build and mature a cybersecurity risk register that serves as the authoritative source of truth for Disney’s threat and control posture, dynamically integrated with threat intelligence, vulnerability management, and third-party risk inputs.
• Drive risk-based prioritization across all InfoSec operational functions (engineering, red team, SOC, cloud security, etc.) - ensuring that every team’s roadmap is anchored in defensible risk reduction rationale, not reactive urgency.
• Develop executive and board-level risk reporting that is clear, credible, and decision-ready; ensure Disney’s risk narrative is consistent from the CISO to the Audit Committee.
• Lead efforts to quantify InfoSec risk in financial terms (FAIR or equivalent), enabling direct comparison of security investment across Disney’s ubiquitous businesses and against measurable risk reduction outcomes.
• Lead a third-party and supply chain risk intelligence capability that goes beyond questionnaire-based assessments by integrating continuous external attack surface monitoring, threat intelligence on vendor compromise activity, and contractual control requirements into a unified third-party risk posture.
• Oversee the development, maintenance, and lifecycle management of enterprise-wide Information Security policies, standards, and guidelines, ensuring they are risk-based, clear, and aligned to business realities (not just regulatory checklists).