Adobe

Director of Data Science – Engineering

Adobe

full-time

Posted on:

Location Type: Office

Location: San Jose • California • 🇺🇸 United States

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Salary

💰 $186,500 - $358,250 per year

Job Level

Lead

Tech Stack

AirflowCloudETLPythonSQL

About the role

  • 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, processes, and development paths.
  • Partner cross-functionally with Product, Engineering, Ops, Finance, and Field teams.
  • 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.
  • 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.
  • Deliver dashboards and executive reporting that influence product and business strategy.
  • Translate complex analysis into clear, actionable recommendations for senior leaders.

Requirements

  • 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.
Benefits
  • Health insurance
  • 401(k) matching
  • Flexible work hours
  • Professional development opportunities

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills
data scienceanalyticsdata engineeringpredictive modelingstatistical methodsmodel evaluationETLELTSQLPython
Soft skills
executive-level communicationinfluencing senior leaderscross-functional partnershipteam leadershipbuilding trusted relationshipstranslating analytics into business insightsscaling data maturitydeveloping processesestablishing team structureactionable recommendations