This role will focus on building, maintaining, and improving business intelligence reporting solutions that help stakeholders make data-driven decisions. The position will work primarily with Power BI, paginated reports, Microsoft SQL Server, and Microsoft Fabric.
This is a hands-on, non-senior BI analyst role reporting to the Director of Business Intelligence. The ideal candidate is comfortable working with business stakeholders, translating reporting needs into clear requirements, validating data, and delivering reliable BI solutions using SQL Server and Power BI.
This position is intended for candidates local to the Bethesda, Maryland area, with limited in-office presence as business needs require.
A day in the life of the BI Data Analyst may include:
- Design, develop, maintain, and enhance Power BI reports, dashboards, semantic models, and paginated reports.
- Write, troubleshoot, and validate SQL queries against Microsoft SQL Server source systems.
- Work with SQL Server views, stored procedures, and existing ETL logic to support reporting and data validation needs.
- Partner with business teams to gather requirements, define KPIs, and translate business questions into reporting solutions.
- Apply dimensional modeling and data warehouse best practices, including facts, dimensions, star schemas, and Kimball-style concepts.
- Support BI solutions in Microsoft Fabric and continue developing hands-on knowledge of Fabric capabilities.
- Perform data validation to confirm the accuracy, completeness, and consistency of reports and dashboards.
- Document report logic, data definitions, business rules, and known data limitations.
- Monitor and improve report usability, data refresh reliability, and performance where appropriate.
- Turn data into actionable insight for business users across Rapid Finance.
About You:
- 3+ years of professional experience in business intelligence, data analysis, reporting, or related work; or 5+ years of relevant experience in lieu of a degree.
- Bachelor's degree preferred in Information Systems, Business Analytics, Economics, Computer Science, Statistics, Mathematics, Finance, or a related quantitative/business field; equivalent practical experience will be considered.
- Hands-on experience building reports and dashboards in Power BI.
- Experience creating or supporting Power BI paginated reports, Power BI Report Builder reports, SSRS reports, or similar operational reporting outputs.
- Strong SQL skills, preferably using Microsoft SQL Server and T-SQL.
- Comfortable working with relational data sources, views, stored procedures, and existing SQL-based ETL logic.
- Understanding of dimensional modeling, data warehousing concepts, facts, dimensions, and star schema design.
- Familiarity with Microsoft Fabric and how it supports data integration, analytics, warehousing, and Power BI reporting.
- Strong communication skills with the ability to work with both business users and technical team members.
- Self-motivated, organized, and able to learn new tools, data sources, and business processes quickly.
Technical skills required:
- Power BI report development, including dashboards, semantic models, DAX basics, and paginated reports.
- Microsoft SQL Server and T-SQL querying.
- Experience reading and troubleshooting SQL Server views and stored procedures.
- Dimensional data modeling and data warehouse best practices, including Kimball-style concepts.
- Familiarity with Microsoft Fabric.
- Data validation, report testing, requirements gathering, and documentation.
Preferred skills and experience:
- Hands-on experience with Microsoft Fabric Data Factory, Data Pipelines, Lakehouse, Warehouse, or related Fabric workloads.
- Experience with Azure Data Factory or similar Microsoft data integration tools.
- Experience with SSRS, Power BI Report Builder, SSIS, or related Microsoft BI tools.
- Experience in fintech, lending, banking, finance, accounting, marketing analytics, or similar data environments.
- Exposure to Agile delivery methods or Kimball SDLC.
- Exposure to Python, R, advanced analytics, forecasting, or predictive modeling is helpful but not required.
