Senior Data Product Manager - San Francisco, Atlanta or Portland (hybrid)

Autodesk Autodesk · Enterprise · AMER - United States - California - San Francisco - One Market, AMER - United States - Georgia - Atlanta - Peachtree St NW, AMER - United States - Oregon - Portland

Senior Data Product Manager to lead the strategy and evolution of a Customer Journey Data Set (CJDS), a next-generation event data product built on telemetry from web platforms and event-driven product applications. This role will own the product vision and roadmap for transforming raw event streams into trusted, governed, AI-ready data assets that power Product-Led Growth (PLG), experimentation, personalization, customer insights, and enterprise decision-making across Autodesk.

What you'd actually do

  1. Define and articulate the vision for the event-driven data product(s).
  2. Identify key personas (analytics, data science, growth, product, ML, exec, etc.) and their needs.
  3. Conduct regular evaluations of changing user needs
  4. Translate business objectives into data product capabilities
  5. Develop and maintain a clear roadmap aligned with measurable outcomes

Skills

Required

  • 7+ years in Product Management, preferably in data, analytics, or platform products
  • Experience working with event-driven architectures and telemetry data
  • Strong understanding of data modeling (event-based schemas, dimensional modeling, semantic layers)
  • Experience collaborating with Architecture and Data Engineering and analytics teams
  • Knowledge of event tracking systems (e.g., web analytics, CDPs, instrumentation frameworks)
  • Strong prioritization and outcome-driven thinking
  • Excellent written and verbal communication skills
  • Proven ability to deliver internal data platforms or data products
  • Excellent communication, stakeholder management, and influencing skills.

Nice to have

  • Background in B2B SaaS or enterprise tech
  • Familiarity with agile methodologies and product discovery frameworks (e.g., JTBD, dual-track agile)

What the JD emphasized

  • AI-ready data assets
  • event-driven data product
  • telemetry data
  • data modeling
  • data engineering
  • analytics
  • data science
  • data product