Top Senior Business Intelligence Jobs in Washington, DC

Design, develop, and maintain enterprise Power BI dashboards and reports. Integrate data from SQL Server, Azure, Excel and other sources, perform data modeling and DAX calculations, validate data, and document data models and reporting logic while partnering with business stakeholders.

Architect and scale a governed BI and analytics platform (Snowflake, dbt, Sigma) to deliver trusted, standardized KPI frameworks and semantic layers. Build high-quality data models, optimize SQL for large datasets, enable self-serve analytics, mentor engineers, drive governance and testing standards, and partner with Product, Data Science, Finance, and business teams. Promote AI-assisted tooling to accelerate analytics delivery and improve metric trust and reporting consistency.

Validate and QA data across UI and API sources, investigate issues, manage taxonomy mismatches, compile non-automated reports, and update/maintain dashboards (Power BI/Tableau). Collaborate with Business Strategy, Investment, and Analytics teams to resolve data and KPI anomalies.

Design, develop, and deploy Power BI reporting and analytics on Snowflake. Migrate OBIEE reports to Power BI, build data models and ETL/ELT pipelines, write DAX and SQL, optimize report performance, ensure data quality, and support stakeholders with documentation and ongoing support.

Senior Power BI developer responsible for building dashboards, scorecards, and analyses that deliver actionable insights. Partner with stakeholders and data architecture to join disparate datasets, ensure data quality, perform ETL, apply advanced DAX/Power Query and SQL, and present recommendations to senior leadership to drive KPI improvements.

Lead BI reporting and advanced analytics to optimize marketing campaigns and ROI. Build dashboards, manage multi-source data, ensure data governance, provide actionable insights, mentor juniors, and partner with cross-functional teams to guide strategy.

Lead BI partner for product teams to design and maintain scalable data pipelines, dbt transformations, data marts, and observability. Translate business needs into analytical frameworks, support A/B testing and ML feature engineering, collaborate on data governance, and champion CI/CD and best practices for analytics engineering.