Monte Carlo Data

Strategic Senior Sales Engineer, EMEA

London, England, United Kingdom

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Not SpecifiedCompensation

Mid-level (3 to 4 years)Experience Level

Full TimeJob Type

UnknownVisa

AI & Machine Learning, Data & Analytics, Enterprise SoftwareIndustries

Requirements

Candidates should have at least 7 years of experience in Sales, Sales Engineering, or Customer Success for a technical product, with previous experience working with data products or solutions highly preferred. A demonstrated track record in an early-stage company or highly ambiguous environment is essential. Candidates must possess a high degree of ownership and a relentless desire to solve customer problems, alongside the technical acumen to understand and explain complex architecture. A firm understanding of cloud data warehousing, data lakes, ETL concepts and workflows, BI solutions, and SQL is required.

Responsibilities

The Strategic Senior Sales Engineer will provide excellent technical guidance and support to the sales team, including delivering demos and managing successful evaluation processes. They will plan production rollouts, position the platform to both technical and non-technical stakeholders, advocate cross-functionally for the customer’s needs, and create content to scale their work. Additionally, they will be responsible for evangelizing the category, owning a high degree of appetite for ambiguity, being part of a high-performing team, and traveling to customer sites up to 25% of the time.

Skills

Cloud data warehousing

Data lakes

ETL concepts

BI solutions

SQL

Technical acumen

Problem-solving

Project management

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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