[Remote] Strategic Sales Engineer at Monte Carlo Data

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

Skills

Key technologies and capabilities for this role

Sales EngineeringProduct DemosTechnical RequirementsBusiness Value AssessmentsTechnical SolutionDataAIProof of ConceptCustomer ChallengesBusiness Objectives

Questions & Answers

Common questions about this position

Is this position remote or does it require being in the office?

The position is remote but requires the candidate to be based in Boston or New York, with up to 25% travel to customer sites.

What is the salary for this Strategic Sales Engineer role?

This information is not specified in the job description.

What skills and experience are required for this role?

Candidates need 5+ years of Sales Engineering experience for a technical product, a firm understanding of data ecosystems including cloud data warehousing, data lakes, ETL, BI solutions, and SQL, plus experience in early-stage or ambiguous environments.

What is the company culture like at Monte Carlo?

Monte Carlo fosters a high-performance team culture in a fast-paced startup environment, emphasizing ambitious goals, high standards, embracing ambiguity, ownership, and relentless problem-solving for customers.

What makes a strong candidate for this Sales Engineer position?

Strong candidates have 5+ years in Sales Engineering, deep data ecosystem knowledge, proven success in startups or ambiguous settings, technical acumen, high ownership, and the ability to manage multiple projects while thriving in fast-paced environments.

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