Data Analytics & Revenue Reporting Specialist
L
LevelUpSaaS revenue analytics
Listing location: Manila; Workplace type: Remote, Aligned with US Central Time (9:00 PM – 6:00 AM PH Time).Part-TimeMiddle
Salary not disclosed
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Job Details
- Languages
- Professional-level written and verbal English communication skills
- Experience
- 2–3+ years of professional experience in revenue analytics, financial data analysis, business intelligence, or SaaS revenue reporting.
- Required Skills
- SQLSalesforceMicrosoft ExcelGoogle SheetsNetSuiteLooker
Requirements
- Have 2–3+ years of professional experience in revenue analytics, financial data analysis, business intelligence, or SaaS revenue reporting.
- Understand SaaS subscription models and metrics including ARR, MRR, Net Revenue Retention, Gross Retention, Churn, ARPU, LTV, and CAC.
- Write complex SQL queries to extract, transform, and analyze data in warehouses such as Google BigQuery.
- Demonstrate expert knowledge of Excel and Google Sheets, including advanced formulas, pivot tables, financial modeling, and scenario testing.
- Have experience constructing, maintaining, and troubleshooting dashboards in Looker, Looker Studio, or comparable BI tools.
- Validate and reconcile cross-system data involving Salesforce, NetSuite, Stripe, and modern ETL/ELT data pipelines.
- Have professional-level written and verbal English communication skills and be able to convey data insights to stakeholders.
- Hands-on familiarity with Stripe billing configurations and transaction structures is a plus.
- Direct working experience with NetSuite ERP module reporting is a strong plus.
- Understanding of go-to-market strategies, customer lifecycle management, and enterprise financial planning is nice to have.
Responsibilities
- Monitor, analyze, and report on SaaS revenue metrics, including new, upgrade, downgrade, expansion, and churned ARR/MRR.
- Build, enhance, and maintain dashboards and reports using Looker Studio, Excel, and Google Sheets.
- Validate data consistency and reconcile discrepancies across Salesforce, NetSuite, Stripe, and BigQuery.
- Quality-assure data feeds, investigate reporting discrepancies, and maintain data integrity across the analytics pipeline.
- Support transformation projects by helping define metrics, refine data models, and establish automated reporting workflows.
- Assist Finance and Revenue Operations with forecasting models, scenario analyses, and customer retention and churn analytics.
- Work with Finance, Sales, Strategy, and Data Engineering to align metric definitions, reporting cadences, and data taxonomy.
- Translate financial datasets into clear recommendations and narratives for leadership and stakeholders.
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