Large Enterprise Account Executive, Pacific Northwest

Seattle, Washington, United States

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Not SpecifiedCompensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Enterprise Software, Data & AnalyticsIndustries

Requirements

Candidates should have at least 7 years of SaaS experience, with a minimum of 5 years in closing roles. Experience selling to Global 2000 companies and familiarity with the C-suite is essential. A demonstrated track record in an early-stage company or highly ambiguous environment is required, along with experience selling complex and technical products to data and engineering teams. Candidates should have a proven history of successfully closing six and seven-figure software cloud deals and experience with target account selling, solution selling, or consultative sales techniques. Knowledge of MEDDPICC and Challenger methodologies is a plus.

Responsibilities

The Large Enterprise Account Executive will develop and execute consultative sales strategies to generate pipeline and drive sales opportunities. They will leverage ABM support to prospect into CTOs and Data Leaders, build strong relationships for growth opportunities, and become a thought leader in how Monte Carlo drives business outcomes for large enterprises. Collaboration across all major internal functional areas and with external partners and customers is essential, as is researching and generating new business opportunities to build and manage a sales funnel and pipeline.

Skills

Enterprise Sales

Strategic/Consultative Selling

Account-Based Marketing (ABM)

CTO Engagement

Data Leadership stakeholder management

Sales Engineering collaboration

Pipeline generation

Forecasting

Upmarket / Large enterprise sales

CRM

Monte Carlo Data

Provides end-to-end data observability solutions

About Monte Carlo Data

Monte Carlo Data helps businesses ensure the reliability of their data through end-to-end data observability, allowing real-time monitoring of data freshness, volume, schema, and quality. Their platform includes tools for incident detection and resolution, which assist analysts in addressing data quality issues efficiently. By integrating with communication tools like Slack and JIRA, it fits seamlessly into existing data management processes. The goal is to help businesses avoid the costs associated with bad data, making it suitable for data-dependent companies across various industries.

San Francisco, CaliforniaHeadquarters

2019Year Founded

$229.6MTotal Funding

SERIES_DCompany Stage

Data & Analytics, AI & Machine LearningIndustries

201-500Employees

Benefits

Remote Work Options

Risks

Increased competition from Cribl and BigEye may impact market share.

Technical challenges in integrating with vector databases could affect performance.

New Chief Revenue Officer may lead to strategic shifts disrupting operations.

Differentiation

Monte Carlo offers end-to-end data observability for real-time data monitoring.

The platform integrates with tools like Slack, Teams, and JIRA for seamless communication.

Monte Carlo's root cause analysis speeds up data quality incident resolution.

Upsides

Growing demand for data observability tools boosts Monte Carlo's market potential.

Integration with vector databases opens new opportunities in AI model development.

Real-time data monitoring solutions are increasingly sought after by businesses.

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