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Monte Carlo Data

End-to-end data observability and incident resolution

Strategic Account Executive

Account ExecutiveConfirmed live in the last 24 hours
Full-timeRemote

About the Job

Requirements

  • A consistent record of winning larger enterprise deals with new logos through complex, multi-year sales cycles and meeting or exceeding quota by building a pipeline rather than expanding an inherited book.
  • Experience selling in the data ecosystem, observability, or infrastructure, with the ability to discuss pipelines, observability, and AI readiness with technical buyers.
  • Ability to identify customer pain, develop champions, build business cases, and hold business conversations with C-level buyers about risk, reliability, and outcomes.
  • Experience succeeding in startup or scale-up environments without a mature playbook, creating urgency for problems without an existing budget line, and responding quickly to coaching.

Responsibilities

  • Prioritize a 50–60-account territory and build a self-sustaining pipeline with an SDR through outbound, account-based marketing, partner co-selling, and AI tools, maintaining 3–4x quota coverage.
  • Engage economic buyers, develop internal champions, and multi-thread every deal.
  • Lead discovery, co-build Business Value Assessments with Sales Engineering, and present the business case to executives.
  • Close six- and seven-figure, multi-year deals through procurement, security review, and legal.
  • Write account plans that expand an initial sale into a multi-department footprint.
  • Share competitive intelligence and deal learnings with Sales Leadership, Product, and Marketing to improve the playbook.

Desired Qualifications

  • Experience with usage-based pricing, or a genuine interest in forecasting when deal size varies with adoption.

About the Company

Monte Carlo Data

End-to-end data observability and incident resolution

Monte Carlo Data provides end-to-end data observability and AI-powered data reliability for real-time monitoring of data quality, freshness, volume, and schema to help data engineers ensure data integrity. Its platform continuously observes data pipelines and datasets, surfaces issues through alerts and dashboards, and includes incident detection and resolution that trigger workflows in tools like Slack, Teams, and JIRA. The service differentiates itself by focusing specifically on data reliability and end-to-end observability with built-in incident management and cross-tool integrations, rather than generic monitoring. The goal is to prevent bad data from affecting business decisions by enabling reliable, transparent, and scalable data operations that teams can trust.

Company size
501-1,000
Company stage
Series D
Total funding
$236M
Headquarters
San Francisco, CA
Founded
2019

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