Head of Data Quality

Snorkel AI Snorkel AI · Data AI · Redwood City, CA +1 · 410 - DaaS Delivery

Snorkel AI is seeking a Head of Data Quality to build and own the quality system for their Data-as-a-Service business. This role involves designing the end-to-end quality architecture for a digital data factory that produces customer-specific datasets at scale, working with human contributors and evolving specifications. The position starts as a Principal IC and is expected to grow into a people-management track, focusing on establishing strategy, standards, processes, metrics, and governance for data quality.

What you'd actually do

  1. Establish Snorkel's quality strategy, standards, and operating model across contributors, datasets, and individual data points.
  2. Build the processes, metrics, and governance mechanisms that enable quality to be measured, scaled, and continuously improved.
  3. Ensure quality is embedded throughout the DaaS lifecycle and reflected in the commitments we make to customers.
  4. Define the standards and operating mechanisms that drive high-quality outcomes across contributors, datasets, and engagements.
  5. Partner across Supply, Expert Contributor Experience, Product, and Engineering to operationalize and scale quality throughout the business.

Skills

Required

  • 8+ years of experience in quality, operations, program management, or a related field
  • track record of building or significantly redesigning quality systems in complex, human-in-the-loop environments
  • Experience defining quality standards, measurement frameworks, and operating processes that drive consistent outcomes at scale
  • Strong analytical and problem-solving skills
  • experience using data to measure performance, identify risks, and drive continuous improvement
  • Demonstrated ability to lead through influence and drive cross-functional initiatives
  • Excellent communication and stakeholder management skills
  • Comfortable operating in ambiguity, establishing structure where none exists, and building systems, processes, and teams from the ground up

Nice to have

  • Experience building or scaling quality programs for AI data, model evaluation, or other human-in-the-loop AI workflows
  • Familiarity with AI-assisted quality methods, including LLM-as-judge, automated review systems, or other model-assisted approaches
  • Experience operating in environments with evolving requirements, complex task types, or rapidly changing definitions of quality
  • Background in consulting, engineering, operations, or other roles that demonstrate strong first-principles thinking and problem solving
  • Master's degree in a relevant field, or an MBA with an operations or quality focus

What the JD emphasized

  • build and own the quality system
  • build quality systems from scratch
  • evolving specifications
  • human-in-the-loop environments
  • AI data and evaluation organizations
  • building systems, processes, and teams from the ground up

Other signals

  • building quality systems from scratch
  • human-in-the-loop environments
  • AI data and evaluation organizations