klaviyo

Lead GTM Data Operations Analyst, AI Workflows

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At a Glance

Location
Denver, Colorado, United States
Experience
3–6 years
Posted
2026-07-20T12:30:10-04:00

Key Requirements

Required Skills

PythonSQLSnowflake

Domain Knowledge

  • Automation
  • Education
  • Engineering
  • Finance
  • Regulatory

Requirements

The function is young, the data has known gaps, and the work is to stabilize and extend, not maintain and optimize.

Success Metrics (6–12 Months)

Pipeline Reliability

Scheduled pipeline runs execute without function-lead intervention; failure-to-resolution cycle time under 24 hours for non-blocking issues.

Agent coverage extended to new data elements as prioritized (measured by number of signals under active detection).

Detection & Resolution Quality

Compensation & Benefits

$124,000

$186,000 USD

This role may require up to 10% travel for purposes such as new hire onboarding, client or partner work if applicable, team meetings, and industry events. Travel is coordinated in advance.

Get to Know Klaviyo

We’re Klaviyo (pronounced clay-vee-oh). We empower creators to own their destiny by making first-party data accessible and actionable like never before. We see limitless potential for the technology we’re developing to nurture personalized experiences in ecommerce and beyond. To reach our goals, we need our own crew of remarkable creators—ambitious and collaborative teammates who stay focused on our north star: delighting our customers. If you’re ready to do the best work of your career, where you’ll be welcomed as your whole self from day one and supported with generous benefits, we hope you’ll join us.

Responsibilities

Sit between AI systems and GTM data.

Operate, tune, and extend our agentic data quality pipeline (detection, enrichment, hierarchy mapping, conflict resolution) so it runs reliably, improves continuously, and expands to cover more of the data landscape.

Own the handoff between automated output and human review, managing quality and throughput with our offshore team.

You don’t build agents from scratch, but you run them, evaluate their output with GTM data judgment, and make them better.