Top Remote Analysis Reporting Jobs in Minneapolis, MN

Conduct research and quantitative analysis related to law school access, affordability, academic and bar success, and legal education value. Clean and organize data, maintain research tools and repositories, create statistical tables and visualizations, advise stakeholders on research methods and data interpretation, and produce briefs, reports, and presentations for policy and practitioner audiences.

Serves as the technical authority for Azure SQL architecture, deployment, security, performance, operations, and migrations supporting federal programs. Designs secure Azure Government database environments, leads on-premises SQL Server migrations, develops T-SQL and data models, builds Azure Data Factory pipelines, implements DevOps and infrastructure automation, troubleshoots incidents, optimizes costs, documents standards, and mentors team members. Collaborates with engineering, architecture, data, and DevOps teams on reliable data platforms.

Build and maintain Power BI dashboards, reports, data models, and SQL-driven datasets supporting marketing and operations decisions. Analyze funnel, conversion, cohort, channel, ROI, LTV, and forecasting performance; validate data across advertising, CRM, and web analytics sources; and identify actionable insights. Contribute to Databricks pipelines, AI-enabled analytics, experimentation, and marketing mix modeling while partnering with stakeholders to deliver accurate, timely, self-service reporting.

Lead design and implementation of tracking with GTM, analyze user behavior in GA4, build BigQuery queries and dashboards, define KPIs with cross-functional teams, troubleshoot tagging/data issues, and perform deep-dive conversion and journey analyses to optimize web and mobile performance.

Own end-to-end client data migrations: reverse-engineer legacy ETL, design and build Airflow DAGs and Spark jobs, validate and reconcile data at scale, document architecture and decisions, and coordinate cross-functional teams through go-live and hypercare.

Supports clients and internal stakeholders by gathering requirements and developing business intelligence, reporting, automation, and low-code/no-code solutions. Creates SQL-based data solutions, reports, dashboards, and visualizations; troubleshoots data and automation issues; and collaborates with infrastructure and development teams to maintain solution stability, performance, and security.

Build and maintain reliable data pipelines supporting money movement, fraud response, and client reporting. Integrate internal and external APIs, orchestrate workflows with Airflow on Kubernetes, and implement testing, monitoring, alerting, and observability. Debug production issues, document root causes, improve pipeline efficiency, collaborate with stakeholders, and contribute to technical designs. The role requires Python, SQL, Airflow, Snowflake, dbt, and GCP experience, with opportunities for increased end-to-end ownership.

Analyze large healthcare datasets, build and implement quantitative models, perform statistical analyses, ensure data accuracy, collaborate with cross-functional teams, and provide actionable insights to improve healthcare delivery.

Designs and stewards enterprise ETL/ELT pipelines, lakehouse, warehouse, and data models using Microsoft Fabric, SQL, and Python. Establishes data quality, testing, lineage, security, governance, DataOps, CI/CD, and performance optimization practices. Uses AI coding and agentic tools for development while reviewing outputs rigorously. Partners with stakeholders to shape requirements, leads complex initiatives, mentors engineers, and collaborates with analysts, data scientists, and BI teams to deliver reliable data products.

Owns executive reporting for autonomous vehicle system performance, including the weekly Software Performance Review and broader commercial readiness analyses. Synthesizes robotics data, diagnostic evaluations, and performance metrics into strategic narratives for senior leadership. The role aligns cross-functional engineering data, automates reporting pipelines and presentation generation, establishes visualization standards, and mentors junior engineers. It requires deep knowledge of robotics, autonomous vehicle performance, data architectures, executive communication, and AI-assisted development workflows.