Vp, Analytics Engineering & Dna Operations

Disney Disney · Media · Glendale, CA +1

The VP of Analytics Engineering & Operations will lead the data intelligence and analytics team for Disney Entertainment's Direct-to-Consumer business, focusing on analytics engineering, DnA operations, and AI analytics capabilities. This role involves defining strategy, overseeing semantic layer and metrics governance, advancing AI initiatives like LLM evaluation and agentic workflows, and ensuring operational excellence and scalability across Disney+, Hulu, and ESPN.

What you'd actually do

  1. Define and communicate the vision, strategy, and multi-year roadmap for DnA Operations and Analytics Engineering, elevating both functions into scalable, AI-enabled capabilities that accelerate decision velocity across DTC.
  2. Lead Analytics Engineering across all verticals and cross-DTC stakeholders, including ownership of the semantic layer, source of truth, metrics governance, BI and reporting, enablement, and AI Analytics, ensuring every metric means the same thing everywhere and is available when, where, and how teams need it.
  3. Lead DnA Operations, PMO, and TPM, ensuring predictable, on-time delivery across cross-DnA programs through operational rigor, risk mitigation, and cross-functional alignment, and ensuring strategic alignment and enablement through standardized operational rhythms, transparent planning, and consistent narratives across DnA.
  4. Advance AI Analytics initiatives, including the development of AI-powered tools and features on foundational models, evaluator frameworks for LLM accuracy and consistency, AI agentic workflows with appropriate guardrails, and third-party analytics tool evaluation, implementation, and governance.
  5. Develop talent through coaching, mentoring, and structured leadership growth, building managers into senior leaders and establishing team culture, identity, and career pathways that blend technical excellence with business acumen.

Skills

Required

  • 12+ years of experience in analytics, analytics engineering, data science, technical program management, or operations roles, with 8+ years in leadership or management
  • Proven success building and scaling analytics engineering, BI, or analytics operations capabilities in product-led organizations.
  • Deep expertise in semantic layer design, metric governance, and ensuring consistency across reporting, analysis, experiments, forecasts, and executive reviews.
  • Strong fluency with analytics tools (SQL, Python/R, Looker, Tableau) and modern data platforms (Snowflake, Databricks, Airflow, AWS or equivalent).
  • Demonstrated experience leading program management, technical program management, or cross-functional operations at enterprise scale.
  • Strategic experience with AI/ML applications in analytics, including AI-powered business intelligence, LLM tool development, evaluator frameworks, or AI agentic workflows.
  • Track record of executive communication and influence across technical and non-technical audiences, with the ability to engage senior stakeholders through data narratives and operational clarity.
  • Proven ability to architect and execute multi-year roadmaps, including the evolution of operating models, methodologies, tools, technology, and data products.
  • Experience leading globally distributed or international analytics teams, or partnering closely with regional teams to localize tools and processes.

Nice to have

  • Advanced degree in Business, Data Science, Economics, Statistics, Computer Science, or a related quantitative or business discipline.
  • Prior leadership experience in the streaming media industry and/or supporting a direct-to-consumer or subscription-based product.
  • Knowledge of subscriber lifecycle, content engagement, retention analytics, and account-based performance analytics.
  • Prior experience leading AI Analytics initiatives, including proprietary AI tools, LLM evaluation frameworks, or AI agentic wo

What the JD emphasized

  • AI Analytics capabilities
  • AI Analytics
  • AI-powered tools
  • evaluator frameworks for LLM accuracy
  • AI agentic workflows
  • third-party analytics tool evaluation
  • LLM evaluation frameworks

Other signals

  • AI-enabled capabilities
  • AI Analytics
  • AI-powered tools
  • evaluator frameworks for LLM accuracy
  • AI agentic workflows
  • third-party analytics tool evaluation
  • LLM evaluation frameworks