Sales Engineer, USA West
AtlanSalary not specified
- Full Time
- Internship
Not SpecifiedCompensation
Junior (1 to 2 years), Senior (5 to 8 years)Experience Level
Full TimeJob Type
UnknownVisa
Data & AnalyticsIndustries
Requirements
Candidates must possess at least 3 years of recent experience directly managing a team of enterprise sales engineers in a fast-paced, matrixed environment, and a minimum of 10 years of full-cycle, B2B sales engineering experience in complex software sales with a proven track record of winning new business at the enterprise and strategic level. Sales engineering experience within the data sector is required, along with an understanding of cloud data warehousing, data lakes, ETL concepts and workflows, BI solutions, and SQL. Strategic account experience with Global 2000 companies and long sales cycles is preferred, and experience working in startup environments and with consumption-based models is strongly desired.
Responsibilities
As a Strategic Sales Engineering Manager, you will evangelize a category with enormous potential, hire and develop a team of high-performing sales engineers, regularly report on team and individual results through inspection and forecasting, identify and make recommendations for improvement in process, efficiency, and productivity, create POV and expansion playbooks to land net new deals and expand within the customer base, build tight partnerships with sales leadership, and understand the challenges facing the team and clear the way to allow for success.
Skills
Team Leadership
Sales Engineering
Enterprise Sales
B2B Sales
Complex Software Sales
Data Sector Knowledge
Cloud Data Warehousing
Data Lakes
ETL Concepts
BI Solutions
SQL
Strategic Account Management
Customer Relationship Building
Process Improvement
Forecasting
Playbook Development
Partnership Building
Change 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