Top Remote Analysis Reporting Jobs in Minneapolis, MN

Build and maintain Tableau dashboards, define KPIs, validate data, and query large datasets with SQL. Analyze cross-channel marketing performance across paid media, CRM, ecommerce, web, and app channels. Translate findings into actionable business insights, recurring client reports, and executive-ready presentations. Collaborate with engineering, analytics, data engineering, and strategy teams while guiding stakeholders toward data-driven decisions.

As the founding engineer of the Data Intelligence team, you will design semantic layers, develop AI tooling, and automate data processes to drive business insights.

The Senior Business Systems Analyst will leverage ServiceNow for automation, aligning solutions with business needs, enhancing user experience and driving AI-assisted solutions.

Lead strategic vision and execution of GitLab's data platform and analytics capabilities, focusing on AI-enabled self-service analytics and data governance.

Lead design and scaling of the data platform and analytics pipelines. Build and maintain ETL/ELT workflows, integrations, serverless data services, and reliable data models. Mentor teammates, improve automation, observability, and data governance to support analytics and operational insights.

Own fraud detection and mitigation for ACH payments: design controls, run investigations, analyze performance (precision/recall, financial impact), and partner with Product, Data Science, Risk ML, and Engineering to operationalize risk strategies and transition to model-driven controls.

Lead analytics engineering for Revenue, Marketing, and Finance by building scalable data solutions, data models, and dashboards; provide training and consultation, support ad hoc data needs, and translate technical findings into executive-level insights to improve operational performance.

Own and evolve the data infrastructure powering identity and fraud products. Build and operate scalable ETL/ELT pipelines, ensure data quality and observability, optimize storage and access, support product squads, respond to production incidents, mentor engineers, and drive data platform innovation.

Lead the Data Platform Engineering team owning ETL/reverse-ETL pipelines, replication, and production datastores. Define architecture, roadmap, standards (IaC, observability, schema contracts), mentor engineers, drive incident response and durable fixes, and partner on cross-team technical decisions and operational reliability for data correctness, completeness, and timeliness.

Lead revenue-cycle performance analyses, diagnose root causes, quantify value (ROI/collections lift), and translate findings into pragmatic, stakeholder-ready recommendations. Partner cross-functionally to scope analyses, validate data, and drive strategic workstreams that inform product roadmap and client outcomes.