Sr Manager, Data Engineering , Amazon Selling Partner Verification

Amazon Amazon · Big Tech · Seattle, WA · Data Science

Lead data engineering, business intelligence, and analytics teams to build scalable data pipelines, analytical frameworks, and enable machine learning models for seller verification and onboarding systems. Focus on data infrastructure, modeling capabilities, and insights to drive verification effectiveness, impacting seller experience and marketplace integrity.

What you'd actually do

  1. Set organizational priorities by balancing customer experience, stakeholder requirements, and business impact. Define success metrics and ensure teams focus on high-leverage work.
  2. Define the long-term technical vision for data infrastructure, analytics, and machine learning enablement. Design systems that scale with business growth and adapt to evolving verification requirements.
  3. Deliver high-quality data engineering solutions including production-grade pipelines, data models, and analytical tools. Build rapid prototypes to validate approaches and gather user feedback.
  4. Collaborate with product and business leaders to translate verification requirements into technical solutions. Partner with science teams to productionize models and with engineering teams to integrate data systems.
  5. Hire and develop talent across data engineering, business intelligence, and analytics disciplines. Build a high-performing organization capable of solving Amazon's most complex verification challenges.

Skills

Required

  • 8+ years of data engineering experience
  • 5+ years of engineering team management experience
  • Experience managing multiple projects and priorities across teams in a fast-paced, deadline-driven environment
  • Experience leading global teams

Nice to have

  • Experience working with data engineers and business intelligence engineers collaboratively
  • 3+ years of identity verification/fraud detection process experience
  • Experience building large-scale machine learning and AI solutions at Internet scale
  • Experience in regulatory compliance management with government agencies

What the JD emphasized

  • 8+ years of data engineering experience
  • 5+ years of engineering team management experience
  • Experience building large-scale machine learning and AI solutions at Internet scale