[Hiring] Data Load Analyst @Everest Search Partners

Role Description

Everest Client seeks a Data Load Analyst for a 6 month fully remote contract role with a SaaS company. As a Data Load & Financial Analyst, you will play a key role in the migration and implementation of an enterprise quoting solution. This role is primarily focused on the extraction, cleansing, and loading of historical pricing and subscription data into Salesforce CPQ, helping to replace a legacy quoting tool with an accurate, scalable foundation. This is an excellent opportunity for a detail-oriented analyst early in their career to gain deep exposure to CPQ systems, SaaS pricing structures, and quote-to-cash processes within a fast-growing FinTech company.

• Extract, organize, and validate historical pricing and subscription data from legacy contracts for migration into Salesforce CPQ
• Perform data cleansing and transformation using Excel or Google Sheets to ensure accuracy and consistency prior to data loads
• Execute structured data loads into Salesforce CPQ, verifying integrity and completeness of records post-load
• Document data mapping, load procedures, and any discrepancies or exceptions encountered during migration
• Partner with Deal Desk, Sales Operations, and Product/Partner teams to clarify pricing data questions and resolve data quality issues
• Support ongoing data validation efforts by comparing legacy records against CPQ outputs and flagging inconsistencies

Qualifications

• 1–3 years of experience in a data, finance, sales operations, or systems analyst role
• Hands-on experience with Salesforce (SFDC) strongly desired; Salesforce CPQ experience strongly preferred as well
• Exposure to CPQ platforms (Salesforce CPQ, Apttus, Conga, or similar) is a plus
• Familiarity with SaaS contracting models, subscription pricing helpful
• Advanced proficiency in Microsoft Excel or Google Sheets (lookups, pivot tables, data manipulation) with strong organizational skills
• Ability to work independently, manage tasks, and meet deadlines with minimal oversight
• Clear written and verbal communication skills for cross-functional collaboration