Large Enterprise Account Executive, TOLA

Austin, Texas, United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Enterprise SoftwareIndustries

Requirements

Candidates must possess at least 7 years of SaaS experience, with a minimum of 5 years in closing roles, and have experience selling to Global 2000 companies. Proven success in engaging with C-suite executives, a demonstrated track record in early-stage or ambiguous environments, and experience selling complex technical products to data and engineering teams are essential. Experience in outbound sales, category creation, or build vs. buy scenarios, along with a history of closing six and seven-figure software cloud deals, is required. Familiarity with consumption models is a plus, as are MEDDPICC and Challenger methodologies.

Responsibilities

The Large Enterprise Account Executive will develop and execute consultative sales strategies to generate pipeline and drive sales opportunities within Global 2000 accounts. Responsibilities include leveraging ABM support to prospect into CTOs and Data Leaders, building strong relationships to foster growth, and establishing thought leadership in data reliability outcomes. This role involves collaborating with internal teams such as sales engineering, marketing, and partnerships, as well as external partners and customers. Additionally, the executive will research and identify new business opportunities to build and manage a sales funnel and pipeline.

Skills

Consultative Sales

Strategic Account Management

Enterprise Sales

ABM

Sales Strategy

CTO engagement

Data Leader engagement

Cross-functional collaboration

Sales Engineering collaboration

Thought leadership

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