Job Overview
Location
New York
Job Type
Full-time
Category
Sales
Date Posted
May 16, 2026
Full Job Description
đź“‹ Description
- • Develop and execute consultative and solution-based sales strategies to generate pipeline, drive sales opportunities, and deliver predictable bookings within the Global 2000 market
- • Leverage account-based marketing (ABM) support to prospect and engage CTOs and other data leadership stakeholders
- • Lead the discovery process to gather Business Value Assessment (BVA) inputs from prospective enterprise customers
- • Co-own the development of BVA presentations and independently present them to executive decision-makers
- • Build and maintain executive-level relationships with key enterprise buyers, positioning yourself as a trusted advisor and thought leader
- • Define and communicate positive business outcomes tied to Monte Carlo’s data observability platform for large-scale AI and data teams
- • Research, identify, and qualify new business opportunities to build and manage a robust sales funnel and pipeline
- • Collaborate cross-functionally with sales engineering, marketing, product, and partnerships teams to align on customer needs and drive deal progression
- • Work closely with external partners and customers to leverage existing wins and scale market share across verticals including finance, healthcare, consumer goods, and media
- • Sell complex, technical SaaS products to data engineering and AI teams, translating product capabilities into enterprise value
- • Close six- and seven-figure software cloud deals with enterprise prospects and customers using consultative sales techniques
- • Utilize target account selling, solution selling, and proven methodologies such as MEDDPICC and Challenger
- • Operate in a fast-paced, high-growth environment with evolving processes, contributing feedback to sales, marketing, product, and engineering teams
- • Maintain a deep understanding of Monte Carlo’s platform and its role in unifying data and agent observability for production AI systems
- • Report directly to a Strategic Sales Leader and operate primarily in the northeast U.S. region, with flexibility for remote work
- • Support the company’s upmarket sales playbook by driving new logo acquisition and expansion within existing Global 2000 customers
- • Represent Monte Carlo as a trusted partner in the data observability space, aligned with the company’s recognition as the #1 Data Observability Platform by G2
🎯 Requirements
- • 7+ years of SaaS sales experience with 5+ years in closing roles
- • Proven experience selling to Global 2000 companies
- • Demonstrated track record of closing six- and seven-figure enterprise software cloud deals
- • Experience selling complex technical products to data and engineering teams
- • Experience in early-stage companies or highly ambiguous environments
- • Experience in outbound sales, category creation, or build vs. buy dynamics
🏖️ Benefits
- • Opportunity to join a fast-growing sales team poised to quadruple over the next few years
- • Work with market-leading enterprise clients including Pepsi, Fox, General Mills, and Amgen
- • Recognition as a top employer: Named 2026 Best Place to Work by Built In
- • Access to a world-class data observability platform recognized as #1 by G2 for four consecutive quarters
Skills & Technologies
See exactly how your profile matches this role — strengths, skill gaps, and what to do about them.
About Monte Carlo Data, Inc.
Monte Carlo Data, Inc. provides a data observability platform that monitors data pipelines, detects anomalies, and alerts teams to data quality issues across warehouses, lakes, and ETL systems. It automates lineage tracking, impact analysis, and root-cause investigation to reduce downtime and improve trust in analytics and machine-learning outputs. The company serves data engineers, analysts, and data scientists in finance, e-commerce, healthcare, and technology sectors, integrating with Snowflake, Databricks, BigQuery, Redshift, and Airflow to deliver real-time reliability metrics and governance controls.
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