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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Analyst, Finance - **Company:** Scale Inc - **Location:** United States (Remote available) - **Experience:** Starter - **Salary:** $80,000.0 - $100,000.0 - **Contract:** Permanent contract - **Skills:** Microsoft Excel, Data Analysis, Business Logic, Microsoft Azure, Spreadsheets, Data Cleansing, Extract Transform Load (ETL), Data Transformation, Python (Programming Language), KNIME, QuickBooks (Software), Raw Data, Power BI, Shopify, SQL Databases, Tableau (Software), Transaction Data, Snowflake, Amazon Marketplace, Pandas, Stripe, Looker Analytics, Alteryx - **Published:** September 28, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=7ce3db6801de047c ## About the Role The Essentials (Experience & Tech Stack) * Experience Level: 2-3 years of specific Data Analysis experience, ideally supporting finance. (We are not looking for Junior Analysts or Senior Data Architects; we need a hands-on mid-level executor.) * Forecasting: Hands-on experience building and maintaining financial forecasts (e.g., revenue, orders, or expenses) in SQL, spreadsheets, or a BI tool. This is required. * Financial Acumen: Comfort with revenue recognition, COGS, gross vs. net sales, and contribution margin. * Industry: Proven experience in DTC E-commerce is required. You must be comfortable with Shopify, Amazon Seller Central, and Stripe data. * Warehousing & BI: Strong proficiency with Snowflake (SQL) and Sigma. We're open to candidates experienced with Tableau, Looker, or Power BI who can adapt quickly. * Spreadsheets: Advanced Excel or Google Sheets skills. * Transformation Tools: Competency in KNIME or dbt is preferred, but we are open to candidates experienced with Alteryx or Python who can adapt quickly. * ELT Familiarity: Awareness of how ELT tools (like Hevo, Fivetran, Airbyte, Azure, etc.) function, so you can communicate effectively with our Data Engineer. ## Description We are looking for a mid-level Data Analyst who is far more than a report builder. You are a "Data Detective" who understands the heartbeat of an e-commerce P&L. You will not just analyze data; you will own the truth behind our revenue numbers and help Finance see what's coming next. We need a Financial Data Master who understands payment processors, core financial concepts, and forecasting, and who knows how raw transaction data becomes a P&L the business can trust. Additionally, you will act as a critical partner to our Finance team, bridging the gap between raw data, payment processors, our financial reporting, and the forecast. What You'll Do 1. Forecasting * Financial Forecasts: Build and maintain forecasts for revenue, orders, subscription renewals, and expenses by brand and channel, and keep them current as actuals come in. * Forecast vs. Actual: Track how forecasts compare to actuals, explain the gaps, and flag meaningful misses to the Finance team. * Budget Support: Update the scenarios and assumptions Finance uses for budget planning. 2. Financial Reporting & Unit Economics * P&L Reporting: Build and maintain reporting on revenue, gross vs. net sales, discounts, refunds, COGS, and contribution margin by brand, channel, and product. * Unit Economics: Report on contribution margin, payback, and profitability by brand, channel, and product. * Month-End Close: Support month-end close with timely, tied-out data. * Budget vs. Actual: Produce variance reporting that explains what moved and why. 3. Financial Data Integrity & Reconciliation * Reconciliation Investigations: Act as the lead investigator for revenue discrepancies. You will reconcile data between payment processors (Stripe, Shopify Payments, Amazon), bank deposits, our internal database, and accounting (QuickBooks) to ensure every dollar is accounted for. * Spend Reconciliation: Reconcile marketing spend across ad platforms and invoices against finance records. * Root Cause Fixes: Work with Finance and our Data Engineer to fix discrepancies at the source. * Metric Definitions: Document the business logic behind financial metrics so every team uses the same definitions. 4. Data Transformation & Visualization * Data Preparation: While we have a Data Engineer managing the infrastructure, you will handle the "last mile" of data prep using KNIME or dbt (or similar tools like Alteryx or Python/Pandas). * Business Logic Application: Write efficient SQL to transform raw transaction data in Snowflake into usable datasets that reflect our financial business rules. * Dashboarding: Design, build, and maintain high-impact dashboards in Sigma for Finance and leadership., * You have built or maintained forecasts that Finance relied on, and you can explain why actuals came in above or below them. * You understand how a Shopify order becomes a processor payout and then a bank deposit, and where fees, refunds, and chargebacks create gaps. * Understanding QuickBooks report structures is a plus. The Financial Mindset * You have the patience and precision to trace a single transaction through the entire data lifecycle to solve revenue mismatches. * You'd rather be right than fast, but you're fast too.