Head of Engagement Management - Data as a Service

Snorkel AI Snorkel AI · Data AI · Redwood City, CA +1 · Remote · 415 - DaaS Sales & Success

This role leads and scales the Engagement Management function for Snorkel AI's Data-as-a-Service business, focusing on customer outcomes, consumption, and revenue realization. It involves building and managing a team, setting strategy, and partnering with Sales, Product, and Engineering to drive growth and customer success in a technical/data-driven environment.

What you'd actually do

  1. Build, lead, and develop the Engagement Management team, including hiring, coaching, and performance management
  2. Define and execute the Engagement Management strategy, aligning team priorities to business goals (consumption, NRR, expansion)
  3. Own overall customer consumption, adoption, and revenue realization across DaaS accounts
  4. Partner with Sales leadership to drive expansion strategy and execution across key accounts
  5. Establish operating cadence, metrics, and reporting to track account health, usage, and revenue performance

Skills

Required

  • 8+ years of experience in customer success, account management, consulting, or similar roles in a technical or data-driven environment
  • 3+ years of experience leading and scaling customer-facing teams
  • Proven track record of driving customer adoption, consumption, and expansion at scale
  • Experience partnering closely with Sales leadership in a shared ownership model of revenue growth
  • Experience leading teams in consumption-based or usage-based business models
  • Experience driving net revenue retention (NRR) and expansion metrics at scale
  • Strong leadership and organizational skills, with the ability to set strategy and execute through teams
  • Experience building processes, playbooks, and operating rhythms in high-growth environments
  • Excellent communication skills, including executive-level stakeholder management
  • Technical aptitude in data, AI/ML, or related domains
  • Ability to operate in fast-paced, ambiguous environments
  • Willingness to travel up to 20%

Nice to have

  • Background in AI/ML, data infrastructure, or data services businesses
  • Experience working in high-growth or early-stage environments building functions from the ground up

What the JD emphasized

  • customer adoption
  • consumption
  • revenue realization
  • expansion
  • net revenue retention (NRR)
  • customer success
  • revenue performance
  • customer outcomes
  • revenue growth
  • consumption-based or usage-based business models
  • driving net revenue retention (NRR) and expansion metrics at scale
  • building processes, playbooks, and operating rhythms in high-growth environments
  • Technical aptitude in data, AI/ML, or related domains