At Disney we’re storytellers. We make the impossible, possible. The Walt Disney Company is a world-class entertainment and technological leader. Walt’s passion was to continuously envision new ways to move audiences around the world—a passion that remains our touchstone in an enterprise that stretches from theme parks, resorts and a cruise line to sports, news, movies and a variety of other businesses. Uniting each endeavor is a commitment to creating and delivering unforgettable experiences — and we’re constantly looking for new ways to enhance these exciting experiences. 

The Enterprise Technology mission is to deliver technology solutions that align to business strategies while enabling enterprise efficiency and promoting cross-company collaborative innovation. Our group drives competitive advantage by enhancing our consumer experiences, enabling business growth, and advancing operational excellence. 

Team Description: 

As a cross-cutting function of the Technology Transformation Office, the Performance Management team’s mission is to enable operational transparency and decision support across complex, cross‑functional technology initiatives. Through reliable, scalable, and well‑governed data foundations, the team creates coherent and performant data assets that underpin insight tools, executive reporting, scorecard, and dashboard visualizations used by senior technology leadership. 

What You’ll Do: 

• Design, build, and maintain data ingestion and transformation pipelines that integrate operational data from tools, systems, and shared file sources into modern cloud data platforms. 

• Develop scalable ETL/ELT processes using Python, SQL, and workflow orchestration tools to support analytics, dashboards, and executive reporting. 

• Create and maintain data models that enable consistent, performant downstream consumption by analytics and visualization tools such as Tableau, Power BI, and Airtable. 

• Implement data quality checks, validation logic, and monitoring to ensure accuracy, reliability, and traceability of data assets. 

• Partner with analysts and stakeholders to understand reporting needs and translate them into well‑structured, reusable data solutions. 

• Support the evolution of ad‑hoc and manual data processes into more automated, standardized, and sustainable patterns over time. 

• Document data sources, pipelines, assumptions, and transformations to support transparency, maintainability, and shared understanding. 

• Use AI‑assisted development tools responsibly to improve productivity, support code development, troubleshooting, and documentation, and continuously refine prompt and validation practices. 

• Operate with a strong sense of ownership for the health, performance, and integrity of the data produced, while building in alignment with established architectural guidance and patterns. 

Required Qualifications & Skills: 

• Minimum of 3+ years of experience in a data engineering, software engineering, analytics engineering, or similar technical role. 

• Proficiency in Python and SQL for data processing, automation, and transformation. 

• Experience building or maintaining ETL/ELT pipelines and working with structured and semi‑structured data. 

• Familiarity with modern cloud data warehouses such as Snowflake and related data tooling ecosystems. 

• Experience working with operational or business data sourced from enterprise tools, shared files, or spreadsheets. 

• Comfort working in iterative delivery models (Kanban and/or Agile) with shifting priorities and stakeholder‑driven demand. 

• Demonstrated ability to write maintainable, well‑documented code with attention to data quality and long‑term sustainability. 

• Practical experience using AI‑assisted tools to support development workflows, including code generation, debugging, and documentation. 

• Strong problem‑solving skills, attention to detail, and the ability to work productively with minimal day‑to‑day technical direction. 

Preferred Qualifications: 

• Exposure to workflow orchestration, transformation, or automation tools such as Airflow/Dagster, dbt, or Power Automate. 

• Experience ingesting and normalizing data from tools such as Jira, ServiceNow, or similar operational platforms. 

• Familiarity with version control systems (e.g., Git) and basic CI/CD concepts. 

• Working knowledge of data modeling concepts and performance optimization techniques. 

• Basic exposure to Java or other JVM‑based languages. 

Required Education: 

Bachelor’s degree in Computer Science, Information Systems, Software Engineering, Electrical or Electronics Engineering, or a comparable field of study, and/or equivalent work experience. 

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