Revenue Operations Analyst
Field NationSalary not specified
- Full Time
- Junior (1 to 2 years)
Not SpecifiedCompensation
Mid-level (3 to 4 years)Experience Level
Full TimeJob Type
UnknownVisa
Consumer Software, Data & AnalyticsIndustries
Requirements
Candidates must have at least 4 years of experience in Revenue Operations, Sales Operations, or Business Intelligence roles. They should possess hands-on experience with SQL for querying, data manipulation, and optimization. Proficiency in Salesforce (SFDC) administration and reporting is required, along with strong skills in Looker for building dashboards and reports. Familiarity with Snowflake or other cloud-based data warehouses is preferred, as well as strong analytical skills and attention to detail. Effective communication skills to work with both technical and non-technical stakeholders are essential.
Responsibilities
The Revenue Operations Analyst will develop dashboards and reports in Looker, SFDC, and Snowflake to track key revenue and sales metrics. They will write SQL queries to extract, manipulate, and analyze data from Snowflake and other databases. The role includes maintaining and improving Salesforce data integrity, automating workflows, and optimizing sales processes. The analyst will support revenue forecasting, pipeline analysis, and performance tracking for sales and go-to-market teams. Additionally, they will identify inefficiencies in revenue operations and recommend scalable solutions while ensuring data quality and compliance across systems.
Skills
Salesforce (SFDC)
Looker
SQL
Snowflake
Data Analysis
Reporting
Data Management
Sales Operations
Revenue Operations
Pipeline Analysis
Forecasting
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