> Markdown version of [/jobs/ext/4674600-power-bi-financial-data-analyst](https://www.wearedevelopers.com/jobs/ext/4674600-power-bi-financial-data-analyst). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Power BI Financial Data Analyst - **Company:** Macpower Digital Assets Edge LLC - **Location:** Louisville, KY, United States - **Experience:** Experienced - **Salary:** $80,000 - $110,000 - **Contract:** Permanent contract - **Skills:** Data Analysis, Analysis of Variance (ANOVA), Data Governance, Extract Transform Load (ETL), Data Transformation, Database Queries, Power BI, SQL Stored Procedures, SQL Databases, Transact-SQL, Microsoft Fabric, Data Management, Data Pipelines - **Published:** November 11, 2026 - **Apply:** https://www.careerbuilder.com/job-details/power-bi-financial-data-analyst-louisville-ky--8b469562-6029-4c92-bad0-51086c55b9e6 ## About the Role Power BI, Financial Analysis, Reporting Dashboards, Power BI, Data Management, SQL (Structured Query Language), Accounting Close, Budgeting, Accounts Receivable, Finance, Power BI Expert Can build polished dashboards independently (DAX, time intelligence, advanced visuals) SQL Pro Writes complex queries (T-SQL, stored procedures, PIVOT) to feed dashboards Finance Fluency Understands AR, budgeting, month-end reporting 3-5+ Years in corporate financial data analysis Nice-to-Have: * Experience with Microsoft Fabric (Lakehouse/Warehouse, Data Factory) * Knowledge of ETL processes & data governance ## Description About the Role: We're seeking a business-savvy Power BI & SQL expert with 3-5+ years of corporate finance data analysis experience to: * Build executive-ready dashboards in Power BI * Design and maintain SQL-driven data pipelines * Transform raw data into actionable financial insights (AR aging, budgeting, month-end close), = Data Analysis & Reporting * Develop real-time financial dashboards (AR aging, revenue trends) * Apply statistics & math (variance analysis, forecasting) to highlight risks/opportunities = SQL & Data Pipeline Management * Write and optimize T-SQL queries for data feeds * Build Fabric Lakehouse/Warehouse models (star schemas, incremental loads)