Top Senior Business Intelligence Jobs in Minneapolis, MN

Lead BI and data for a large real estate account: design and deliver Power BI dashboards, data governance, integrations, SharePoint and automation solutions, build analytics roadmap, translate data into executive insights, drive process improvement, and lead a technical analytics team.

Own end-to-end BI projects: build and maintain dbt models and SQL pipelines in Snowflake, architect OMNI dashboards, ensure data quality, automate reporting, apply statistical methods for insights, lead ROI and causal analyses, and partner with finance, GTM, and customer success to drive data-informed decisions.

Design, build, and maintain Power BI dashboards and data models using Snowflake and other cloud sources. Collaborate with data engineers/ETL teams, gather stakeholder requirements, implement DAX and Power Query transformations, ensure data governance and performance, and deliver analytics within Agile processes.

Lead development and governance of the supply chain data warehouse and analytics platforms. Build SQL-driven models, dashboards, and KPIs to drive inventory optimization, cost reduction, supplier performance, and working capital improvements. Support ERP integrations and data migrations, perform deep data discovery and predictive analytics, and present actionable insights to senior leaders to enable strategic decision-making.

Own and cleanse payments data to produce accurate Power BI dashboards and forecasts. Analyze interchange, ACH, VCC, and check costs to identify margins and optimization opportunities. Deliver executive-level storytelling, perform rigorous reconciliations, and act as an internal consultant to guide resource allocation and reduce payment costs.

Manage and optimize the Business Intelligence engineering team, develop BI strategy, oversee project management, and ensure data accuracy.

Manage a team of analysts for PBM analytics, driving insights and scalable data products. Partner with business leaders for effective reporting and analysis.

The Senior Data Analyst will deliver analytics solutions, develop KPIs and dashboards, conduct advanced analysis, and mentor junior analysts while collaborating with stakeholders.

The Power BI Developer designs and deploys interactive reports and dashboards, collaborates with stakeholders, ensures data quality, and optimizes reporting performance.

The Power BI Developer designs, develops, and deploys interactive reports and dashboards using Power BI, ensuring data quality and providing BI solutions to support decision-making.

As a Business Intelligence Data Scientist, you will develop dashboards, build statistical models, and analyze product features to enhance user insights.

The Business Intelligence Senior Consultant develops BI strategies, implements solutions using Ellucian tools, and supports higher education clients with technical and functional consulting.

The Business Intelligence Analyst will analyze pharmaceutical transaction data, develop visual data models, and collaborate cross-functionally to drive insights and improvements in business strategies.

The Director of Data Analytics & Business Intelligence leads analytics functions, building models and dashboards while guiding a team. Responsibilities include analytics infrastructure management, cross-functional collaboration, and driving AI/ML initiatives.

Lead BI work for Encounter Submissions, analyze and visualize Medicare submission metrics, track HCC identification and closure, provide executive insights, advise cross-functional teams, and manage a team of five data analysts to deliver actionable analytics and reporting.

The Business Intelligence / Data Analyst will optimize the data reporting pipeline using Google Big Query and Omni, work with product management, implement reports, and conduct ongoing maintenance.

The Market & Business Intelligence Manager will lead analytics strategies, manage a team of business analysts, and provide insights to support firm strategy and decision-making.

The Senior BI Analyst will gather requirements, develop scalable reporting solutions, and create dashboards using Power BI, ensuring data-driven decisions across the organization.

Lead and grow a BI and analytics team to build scalable, AI-enabled reporting and self-service analytics. Partner with cross-functional stakeholders to deliver executive dashboards, standardize metrics, ensure data quality and governance, and use AI tools to automate insights and accelerate dashboard development.

Design, build, and maintain scalable AWS data pipelines, data lakes, and warehouses; develop ETL/ELT processes; create and manage AWS QuickSight dashboards (including RLS, embedding, Topics/Spaces, and QuickSight Q); ensure data quality, governance, security; optimize performance; collaborate with stakeholders and support production reporting.

Design, build, and maintain data pipelines, dashboards, and predictive models. Analyze large datasets to generate actionable insights, collaborate with stakeholders, ensure data quality and governance, and document/share analytics best practices to support Marketing, Product, Operations, and Workforce teams.

Lead complex healthcare data analysis and profiling across disparate sources to create source-to-target mappings, rewrite/redirect BI reports and semantic data views, gather and document business/technical requirements, and lead the work unit to ensure transformed reports meet business needs.

The Senior BI Analytics Engineer will design and deliver data models for analytics, ensuring data quality, and collaborating across teams to enhance AI-driven reporting and querying capabilities.

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.