Monte Carlo Data

Strategic Sales Engineer

Boston, Massachusetts, United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Data Science, Artificial Intelligence, Enterprise SoftwareIndustries

Requirements

Candidates should possess 5+ years of experience in Sales Engineering for a technical product, demonstrating a firm understanding of data ecosystems including cloud data warehousing, data lakes, ETL concepts, BI solutions, and SQL. They must have a proven track record in an early-stage company or ambiguous environment, coupled with a high degree of ownership, a relentless desire to solve customer problems, and the ability to connect technical solutions to business value.

Responsibilities

As a Strategic Sales Engineer, the individual will travel to customer sites up to 25% of the time to deliver in-person engagements and build relationships, lead high-impact product demos tailored to customer challenges, drive the discovery process alongside AEs, define technical requirements and use cases, co-develop Business Value Assessments (BVAs), present BVAs to executive stakeholders, embrace ambiguity, contribute to a high-performance team culture, build and nurture technical champions in accounts, partner closely with sales to shape account strategy, and accelerate revenue.

Skills

Sales Engineering

Product Demos

Technical Requirements

Business Value Assessments

Technical Solution

Data

Proof of Concept

Customer Challenges

Business Objectives

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.

Key Metrics

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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