Top Business Intelligence Jobs in Minneapolis, MN

Leads global consumer, market, competitive intelligence, and analytics initiatives. Translates complex data into recommendations for brand strategy, innovation, pricing, marketing, investment, and business planning. Oversees marketing measurement, ROI, brand health tracking, advanced analytics, governance, AI-enabled analytics, and external research partnerships. Influences senior stakeholders across functions and regions while building scalable insights and analytics capabilities.

Build and maintain branch network performance reporting, dashboards, semantic models, and analytical datasets using SQL and Alteryx. Translate banker, branch, market, and enterprise data into actionable insights for senior leaders. Lead analytical projects, manage timelines, communicate executive-ready findings, improve reporting processes, and mentor junior analysts. Partner with Distribution and Consumer Bank leadership in a hybrid, primarily onsite environment.

Design, develop, and maintain data pipelines, ETL processes, integrations, data infrastructure, and complex data models. Build and support data warehouses and analytics solutions using SQL, PL/SQL, Oracle, Snowflake, and cloud technologies. Collaborate with analysts, architects, developers, data scientists, and business stakeholders throughout the delivery lifecycle. Provide production support, troubleshoot issues, tune database performance, and contribute to data-driven reporting and AI tools.

Analyzes complex automotive data, standardizes datasets and KPI definitions, partners with engineering and governance teams, and develops scalable self-service dashboards. The role translates ambiguous business needs into data requirements, automates digital analytics programs, investigates trends and attributes, and supports enterprise reporting. It requires SQL, Excel, data visualization, statistical analysis, and AI tool experience. The position is hybrid, requiring at least 10 office days monthly, with travel up to 10%.

Leads the enterprise business intelligence and analytics strategy, roadmap, reporting, dashboards, KPI frameworks, predictive analytics, data governance, and responsible AI practices. Advises executives, oversees analytics delivery and team development, strengthens data quality and self-service reporting, manages priorities and vendors, and drives cross-functional adoption of data-informed decision-making across the credit union.

Nine-week hybrid technical internship supporting data analytics, business intelligence, product management, software engineering, automation, and technology operations. Interns may develop and maintain reports, dashboards, data models, or product features; assist with automation and process improvement; perform data validation and analysis; document technical processes; collaborate with technical teams; and present project findings. Applicants must be enrolled college students, available for at least eight weeks, and able to work in the office at least three days per week.

Conduct geospatial and molecular HIV data analysis using R, SQL, or Python; manage, merge, validate, and document datasets; support data governance, reporting, and dissemination; and develop or maintain Power BI dashboards. Collaborate with analysts, review data quality issues and error logs, document corrections, and provide project updates while supporting CDC public health surveillance initiatives.

Develops business intelligence solutions using data from diverse sources to deliver insights, visualizations, process automations, and decision support. The role analyzes complex business opportunities, integrates and refines organizational data, presents findings to senior leaders, and recommends technical approaches with minimal direction. Preferred experience includes SQL, Python, Databricks, Power BI, Power Apps, Power Automate, predictive modeling, and healthcare analytics.

Develop and maintain Power BI dashboards, reports, KPIs, and business systems supporting commissioning, quality, and infrastructure projects. Gather requirements, improve workflows and data quality, coordinate user acceptance testing, manage enhancement requests, and validate reporting accuracy. Collaborate with operational, engineering, construction quality, and regional stakeholders to support governance, project readiness, issue tracking, and data-driven decision-making. Create documentation, training materials, and communications for system releases and reporting changes.

Build and maintain data pipelines, SQL queries, data models, database structures, and centralized data warehouse capabilities. Clean and validate data, develop reporting datasets and solutions, support KPI tracking and historical analysis, and collaborate with Finance and Revenue Operations. Investigate data gaps, troubleshoot integrations, and independently deliver reliable technical solutions.

Develops, validates, documents, deploys, and maintains Amazon QuickSight dashboards in a secure CMS environment. Translates stakeholder requirements into interactive visualizations, performs SQL-based ETL and data-quality validation, supports Tableau analytics, manages UAT and dashboard lifecycles, troubleshoots technical issues, and documents data workflows. The role collaborates with analysts, data scientists, CMS stakeholders, QIO staff, and other teams while supporting healthcare and regulated data initiatives.

Transforms business questions, freight market data, and external signals into strategic insights. Builds dashboards, KPIs, forecasting models, predictive analytics, and scalable self-service tools using SQL, BI platforms, cloud data platforms, and scripting languages. Integrates market intelligence and generative AI, validates analytical outputs, and communicates recommendations through executive-ready narratives and visualizations to support commercial strategy, forecasting, and operational performance.

Owns Power BI reporting and analytics for Digital, including internal dashboards, campaign pacing, client-facing intelligence products, contact data health, and data delivery monitoring. Builds DAX reporting logic, automated alerts, budget tracking, segmentation, benchmarking, and trend analysis. Partners with IT, Data Engineering, CRM, and audience teams while transitioning an externally developed platform in-house. Serves as the senior reporting subject matter expert for stakeholder and client-facing analytics.

Supports the development and maintenance of Qlik dashboards, reports, and data visualizations. Performs data analysis, validates reporting outputs, identifies trends and anomalies, translates business requirements into reporting solutions, troubleshoots data issues, and helps maintain metrics and KPIs. Collaborates with business stakeholders and develops knowledge of organizational data sources, business intelligence practices, and data governance standards.

Design and build Account 360 data architecture, predictive pipelines, and automated enrichment workflows using enterprise, telemetry, and software usage data. Apply Python, R, SQL, machine learning, NLP, and process mining to deliver insights, segmentation, scenario planning, and product optimization. Collaborate with R&D, Product, Sales, Marketing, and Service teams while rapidly deploying data products, managing sprint capacity, reducing technical debt, and supporting cross-training.

Own executive, board, investor, financial, and operational reporting for leadership. Build scalable dashboards, define consistent KPIs, reconcile data across systems, investigate performance changes, and translate complex business questions into actionable insights. Partner with Strategy, Finance, and senior leaders to automate recurring reporting, improve data accuracy, and support actuals-versus-budget-versus-forecast analysis.

The Senior Data Analyst will develop and improve Sigma dashboards, reporting, and business intelligence capabilities. Responsibilities include gathering stakeholder requirements, querying and analyzing complex datasets with SQL, improving data quality and governance, defining metrics, automating reporting processes, and partnering on Snowflake data modeling and warehouse improvements. The role also evaluates analytics tools, delivers actionable insights, and communicates findings to technical and non-technical audiences.

Develop dashboards, reporting, and analytics solutions for business teams; monitor performance trends, data quality, risks, and key metrics; investigate complex questions; support A/B testing and instrumentation; and communicate actionable insights to technical and non-technical stakeholders. The role also requires expertise in profit drivers, unit economics, campaign and funnel performance, and the company’s analytics infrastructure.

Develop and maintain Power BI reports, dashboards, visualizations, semantic models, and analytics solutions. Translate business requirements into scalable technical solutions, optimize queries and data models, ensure reporting accuracy and performance, and support data governance. Serve as the primary liaison for business users, provide training and troubleshooting, manage tickets, and collaborate with Data and QA teams. The role also advances AI and machine learning capabilities, mentors colleagues, and contributes to automation, documentation, and code reviews.

Develop and maintain enterprise Power BI dashboards, semantic models, and reporting solutions. Integrate Azure and Databricks data, write Python and PySpark transformations, optimize DAX and data models, implement security, and ensure data quality. Collaborate with stakeholders, engineers, and architects to translate requirements into scalable solutions. Lead technical teams, conduct architecture reviews, manage Fabric platforms, and train business users on Power BI.

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.

Design and build PerfectServe’s unified cloud data platform, including ingestion pipelines, integrations, data models, metrics, and consumer-facing data layers. Establish architecture, engineering, quality, and testing standards; enable safe extraction from production systems; partner with data users; and mentor data engineers. The role requires substantial cloud data platform experience, deep SQL, warehouse expertise, ELT, change-data-capture, AWS, modeling, orchestration, and data quality skills.

Designs and develops enterprise data engineering solutions, pipelines, integrations, and resilient software platforms. Leads architecture, technology strategy, DevOps, incident resolution, vendor evaluation, engineering standards, and cross-team collaboration. Provides technical leadership and mentorship while working with big data, cloud, streaming, data warehousing, CI/CD, infrastructure as code, and modern data stack technologies.

Design and maintain enterprise business intelligence platforms, including dimensional models, semantic layers, data warehouses, Power BI solutions, and Microsoft Fabric integrations. Optimize SQL, DAX, refresh processes, and semantic model performance. Establish BI governance, security, deployment pipelines, source control, testing, monitoring, and documentation. Lead complex initiatives, evaluate emerging technologies, and translate business needs into scalable solutions while communicating technical recommendations and risks to diverse stakeholders.

The Business Intelligence Analyst queries cloud data, builds dashboards and recurring reports, validates data integrity, and delivers actionable insights to business leaders. The role embeds AI tools into reporting, documents data definitions and processes, automates manual work, and partners with FP&A, Business Operations, and Data Engineering. It requires SQL, Excel, BI reporting experience, and practical AI application, with Python, R, Git, and dbt listed as preferred skills.