*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. Key Responsibilities & Duties - 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

• Collect and compile data from various sources, ensuring accuracy and completeness • Maintain and update organizational dashboards • Analyze data to identify trends, patterns, and anomalies • Develop and maintain regular reports, dashboards, and visualizations to support decision-making • Create ad hoc reports as needed for special projects or inquiries • Perform data validation and cleaning to ensure data quality • Monitor data quality metrics and implement improvements as necessary • Work closely with cross-functional teams to understand data needs and provide analytical support • Present findings and insights to stakeholders in a clear and understandable format • Identify opportunities to streamline data collection and reporting processes • Implement automation where possible to improve efficiency and reduce errors • Ensure all data handling practices comply with company policies and relevant regulations • Maintain the confidentiality and security of sensitive data

• Analyze metrics to continually improve core and adjacent products • Contribute to business operations, such as costing, production metrics, planning, and budgeting for new product initiatives • Work cross-functionally to improve the analysis and presentation of products • Monitor the market, competitor activities, any price movements, and make recommendations that will be used in key decision-making • Liaise with other departments to enhance and increase efficiency of effecting price changes in accordance with market shifts • Drive consumer intelligence through development of external and internal data sources that improve business’s understanding of product’s market, competitor activities, and consumer activities • Measure and monitor product or service’s performance, and present consumer, market, and competitive intelligence for product growth • Develop or adopt research tools, sources, and methods that further support and contribute to product marketing management intelligence • Formulate ways to package and market products in a compelling manner • Perform initial product analysis to assess need for requested changes and their potential impact • Support product team in product decisions using quantitative data

• Partner with key stakeholders, including the business unit leaders, Product, Data & Technology teams, to assess their data and analytics needs by eliciting data requirements, and researching internal systems of record and publicly available data sources and assessing their quality of data. • Requisition and obtain private data sources to support business needs for data and insights. • Identify translation or transformation requirements for sourced data into the data warehouse. • Improve quality of sourced data by data curation and validation rules as well as maintaining the Master Data tables. • Maintain the Logical Data Dictionary (LDD) with data lineage information (field definition, domain, source system, intermediary and destination system(s), translations, transformation rules, display screens, referenced reports, etc.), Data Stewards and Data Custodian info along with versioning for historic analysis and audit trail. • Ensure consistent delivery of high-quality insights to key stakeholders by reconciling and validating dashboards and reports in a timely manner. • Document functional / non-functional business requirements for collecting, loading, transforming, curating, processing data and for visualization and distribution of insights. • Identify internal process improvements for automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc. • Provide actionable insights using analytics tools into customer acquisition, operational efficiency and other key business performance metrics. • Identify Personally Identifiable Information (PII) data in primary data sources as well as in data architecture, define masking and other data processing rules for special handling of PII data as well as maintain access control lists for visibility of PII data on a need-to-know basis. • Identify and document the Business Continuity Plan/Disaster Recovery (BCP/DR), and technical requirements for high availability and recoverability for the data architecture. • Improve the quality of data used for analysis by assessing the accuracy of new data sources and the effectiveness of new data gathering techniques. • Define Key Performance Indicators (KPIs) and document technical processes to monitor and analyze data warehouse performance and data accuracy. • Contribute to the team of data professionals by using expertise to answer questions and sharing templates, reusable artifacts with less experienced teammates, enhancing skillsets and competencies of team members, and sharing business domain knowledge throughout the team. • Participate in stakeholder reviews and design sessions. • Provide data, reports, and information to management as needed. • Identify, track, and monitor trends and avoidable technology-related errors; work across functions to develop complex solutions, improvements, and stop-gaps. • Focus on the continual improvement of policies, procedures, and processes falling under scope of authority. • Use expertise to resolve high level issues that cannot be solved by teammates. • Stay abreast of latest technology trends and participate in high-level decisions impacting the direction of Information Technology function. • Consistently monitor and model platform usage, database sizes, compute resources and third- party costs to ensure that the data team’s spend is as cost-efficient as possible. • Champion data transformation to new ways of working and generating insights. • Drive strong communications, partnerships, and stakeholder management with senior leaders, functional managers and staff. • Perform other duties as assigned.