Director of Data Science & Engineering

Adobe • San Jose, CA

2d

About The Position

The Adobe Experience Platform (AEP) Product Success Engineering (PSE) team is seeking an innovative 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.

Requirements

• Bachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative field, with 10+ years of experience in data science, analytics, or data engineering, including 5+ years in people leadership roles managing teams of 10+.
• 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 the ground up.
• Deep technical proficiency across the modern data stack, including 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 integrating diverse SaaS data sources (usage, clickstream, entitlements, cost, CRM, and support).
• Strong background in B2B SaaS metrics, product analytics, customer lifecycle insights, and operating in high-growth, data-driven 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.

Responsibilities

• 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.
• Build and grow a world-class 20+ person data organization.
• Establish team structure, operating processes, and career development paths.
• Partner cross-functionally with Product, Engineering, Operations, Finance, and Field teams.
• Architect end-to-end data pipelines, cloud data warehouse solutions, and real-time and batch analytics.
• Implement data quality, governance, privacy, and metadata standards.
• Enable scalable BI, ML, experimentation, and self-service analytics capabilities.
• Develop models for customer health, adoption forecasting, and expansion.
• Build KPI frameworks for product usage, retention, platform performance, and operations.
• Drive advanced analytics, including segmentation, funnel insights, causal analysis, and experimentation.
• Deliver dashboards and executive reporting that influence product and business strategy.
• Translate complex analyses into clear, actionable recommendations for senior leaders.

Benefits

• Comprehensive benefits programs

What This Job Offers

• Job Type: Full-time
• Career Level: Director