Manager- Analytics & Reporting

The Walt Disney CompanyLake Buena Vista, FL
19h

About The Position

In this role, you will inspire and lead Worldwide Safety & Auditing’s (WSA) Analytics and Reporting Team to transform raw data into actionable insights that guide business strategy. This role serves as a bridge between Safety technical data infrastructure and executive decision-making. You will guide the team to apply statistical methods, perform exploratory analysis, identify trends/anomalies, and building predictive models. You will manage data and analysis utilizing data lakehouse architecture, integration and cross correlation of multiple data streams, leverage statistical methods, artificial intelligence (AI), and machine learning methods to render predictive/leading indicators. Examples of reports generated and distributed include Executive dashboards, Safety, Health Readiness and OSHA dashboards, downtime, labor, legal reports, and other various reports centered around driving Safety and continuous improvement across the organization. You will report to Senior Manager-Tech Development & Reporting Analytics

Requirements

  • Analytics, Trending & Reporting Proven ability to define KPIs/metrics, detect trends in complex datasets, and produce executive-ready dashboards and written insights that inform decisions.
  • Expert data storytelling—able to translate complex analysis into clear recommendations for technical and non-technical stakeholders.
  • Statistical & ML Foundations Hands-on proficiency with statistical analysis and predictive modeling (e.g., regression/classification, feature selection, model validation, experimentation A/B testing).
  • Data Platforms & Engineering (Modern Data Stack) Hands-on experience with Snowflake, Airflow, dbt and modern ELT patterns. Advanced SQL and experience building reliable ELT pipelines on cloud data warehouses (e.g., Snowflake). Experience operationalizing dashboard usage metrics for data products and dashboards. Experience designing semantic/metrics layers to enable governed self-service analytics.
  • AI tool assessment, development, and deployment in the data analytics environment Hands-on experience in the use the following applications and environments: Service Now, SharePoint, Maximo, BusinessObjects, Tableau, PowerBI, OpSheet, Snowflake, AWS, Splunk, Airflow, Grafana, and Apex.
  • Bachelor’s degree in a quantitative field (Statistics, Data Science, Computer Science, Engineering) or equivalent experience.
  • 5–8+ years in analytics/data science, including 2–3+ years leading analytics/data science teams or squads.

Nice To Haves

  • Previous technology role with increasing levels of responsibility.
  • Experience with Artificial Intelligence, and Machine Learning – specifically Natural Language Processing.
  • Experience with AWS Environments and Kubernetes / Airflow or other orchestration tools.
  • Experience with accelerated development tools like Cursor.
  • Experience with JavaScript / Django and UI/UX Design.
  • Advanced degree a plus.
  • Certifications (e.g., AWS/Power Platform/Tableau, dbt Analytics Engineering) or equivalent portfolio.

Responsibilities

  • Team Leadership & Development: Recruit, train, and mentor a team of data analysts. Delegate tasks, set deadlines, and monitor project progress. Conduct performance evaluations and provide technical guidance on methodologies.
  • Strategic Planning: Work with WSA Leadership and Define metrics (KPIs) and data analysis strategies. Identify and prioritize high-ROI analytics projects based on business needs. Align analytics initiatives with overarching organizational goals.
  • Data Governance & Quality: Establish standard operating procedures for data collection, cleaning, and analysis. Ensure data accuracy, integrity, and compliance with regulations. Perform periodic risk assessments and initiate risk control strategies. Ensure reporting continuity and performance optimization. Verify report utilization and audit trends to alert stakeholders and leadership of exceptions, decreased performance or other abnormalities. Manage and optimize infrastructure for data intake and engineering.
  • Stakeholder Management: Act as a liaison between technical teams and non-technical stakeholders. Translate complex findings into digestible reports, presentations, and data stories. Secure "buy-in" from senior leadership for data-driven recommendations. Focus on strategies to improve quality of service, consistency and cost.
  • Technical Oversight: Oversee the selection and implementation of analytics tools (e.g., Tableau, Power BI). Lead the design of database systems and reporting dashboards. Stay updated on industry trends, such as AI, machine learning and big data tools. Create and manage data roadmap to ensure AI ready data and data products meeting the standards of Data Products and Platforms (DPP).
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