Adobe-posted 13 days ago
Full-time • Director
San Jose, CA
5,001-10,000 employees

Our Company Changing the world through digital experiences is what Adobe’s all about. We give everyone—from emerging artists to global brands—everything they need to design and deliver exceptional digital experiences! We’re passionate about empowering people to create beautiful and powerful images, videos, and apps, and transform how companies interact with customers across every screen. We’re on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity. We realize that new ideas can come from everywhere in the organization, and we know the next big idea could be yours! About the Role: The Adobe Experience Platform (AEP) Product Success Engineering (PSE) team is seeking an innovative Director of Data Science & Engineering t is seeking a Director of Data Science & Engineering to build the data foundation, KPI frameworks, and predictive intelligence that power product adoption, customer health, platform performance, and operational efficiency. This is a high-visibility, 0-to-1 leadership role responsible for unifying Adobe’s product usage data and delivering insights that transform how we measure customer value and drive product success. You will lead a multidisciplinary team of Data Scientists, Analytics Engineers, and Platform Engineers to architect scalable data systems, develop predictive models, and enable data-driven decision making across Adobe’s AEP portfolio.

  • Data Strategy & Architecture Define and deliver the data science, analytics, and platform strategy for Product Success Engineering.
  • Build a unified data foundation and governance model across diverse data sources.
  • Evolve internal intelligence into customer-facing insights and dashboards.
  • Team Leadership Build and grow a world-class 20+ person data organization.
  • Establish team structure, processes, and development paths.
  • Partner cross-functionally with Product, Engineering, Ops, Finance, and Field teams.
  • Data Platform & Engineering Architect end-to-end pipelines, cloud data warehouse solutions, and real-time/batch analytics.
  • Implement data quality, governance, privacy, and metadata standards.
  • Enable scalable BI, ML, experimentation, and self-service analytics.
  • Data Science & Analytics Develop models for customer health, adoption forecasting, and expansion.
  • Build KPI frameworks for product usage, retention, platform performance, and operations.
  • Drive advanced analytics (segmentation, funnel insights, causal analysis) and experimentation capabilities.
  • Business Intelligence & Insights Deliver dashboards and executive reporting that influence product and business strategy.
  • Translate complex analysis into clear, actionable recommendations for senior leaders.
  • Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or related quantitative field, with 10+ years of experience in data science, analytics, or data engineering roles, including 5+ years in data leadership positions managing teams of 10+ professionals
  • 5+ years of hands-on experience in data science and ML, with expertise in predictive modeling, statistical methods, and model evaluation.
  • Proven 0-to-1 data leader with a track record of building data foundations, teams, and analytics capabilities from scratch.
  • Deep technical proficiency across the modern data stack: ETL/ELT, cloud data warehouses, dbt, Airflow, SQL, Python, ML frameworks, BI tools, and data governance.
  • Experience architecting large-scale cloud-native data platforms, real-time and batch pipelines, and working with diverse SaaS data sources (usage, clickstream, entitlements, cost, CRM/support).
  • Strong background in B2B SaaS metrics, product analytics, customer lifecycle insights, and operating in high-growth or data-driven tech environments.
  • Executive-level communicator with the ability to influence senior leaders, translate analytics into business insights, and build trusted cross-functional partnerships.
  • Demonstrated success hiring and leading multidisciplinary data teams while scaling data maturity from foundational reporting to advanced analytics and predictive intelligence.
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