Top Analysis Reporting Jobs in Minneapolis, MN

Leads geospatial and GIS projects using the Esri platform to create maps, dashboards, spatial analyses, and field data solutions. Manages spatial data quality, project budgets, timelines, client relationships, proposals, and multidisciplinary deliverables. Advises clients on geospatial technologies and serves as a GIS project lead while supporting environmental assessments, infrastructure, permitting, and resource-planning projects.

Leads a data engineering team responsible for designing, developing, testing, deploying, and maintaining scalable data products and platforms. Sets technical direction, manages team performance and development, establishes engineering standards, and oversees data quality, security, governance, and operational excellence. Partners with product owners, enterprise architecture, information security, data governance, and business stakeholders to deliver data solutions. Defines team strategy and roadmap, evaluates emerging technologies, and communicates metrics and progress to senior leadership.

Leads end-to-end data engineering solutions across multiple client engagements, from discovery and architecture through production support. Designs and optimizes Snowflake data platforms, models, warehouses, ELT/ETL pipelines, APIs, integrations, and deployments. Provides technical leadership, client communication, estimation, governance, performance and cost management, engineering standards, mentoring, training, and production escalation support.

Defines and evolves enterprise data architecture supporting analytics, reporting, governance, integration, and AI capabilities. Designs scalable Lakehouse and Medallion architectures, data models, contracts, APIs, and event-driven integrations. Establishes governance standards and trusted data products while aligning platform investments with business and regulatory needs. Leads modernization initiatives, develops data strategy and roadmaps, supports KPI frameworks, mentors technical talent, and guides distributed engineering teams.

Lead architecture and vendor selection for RSM's Martech stack: optimize Adobe Customer Journey Analytics, select and implement a CDP, evaluate journey orchestration, define integration patterns, data model, identity resolution, governance, and activation across CRM, analytics, and marketing systems to enable ABM and personalized buyer journeys.

Produces and distributes daily, ad hoc, trending, and summary reports. Analyzes reporting data, responds to client inquiries, consults with business leaders, develops and maintains reporting processes, and improves reports using new data sources. Coordinates with project managers, verifies electronic reports, manages production schedules, and supports reporting solutions aligned with customer business goals.

Develop and govern enterprise conceptual, logical, and physical data models across business domains. Establish modeling standards, metadata practices, data definitions, and governance processes. Design integration patterns supporting ERP, CRM, cloud, warehouse, data mesh, and data fabric environments. Collaborate with business and technical stakeholders, optimize data structures, document lineage, mentor junior professionals, and ensure model alignment with enterprise architecture and data strategy.

Supports customer analytics and commercial economics by applying AI modeling, SQL, Excel, and business intelligence to identify revenue, retention, margin, bundling, cross-sell, and expansion opportunities. Extracts and validates data from disparate sources, identifies behavioral patterns, builds forecasts, and delivers actionable insights to Sales, Marketing, Product, Revenue Operations, and Lifecycle teams. The role influences commercial and go-to-market decisions across customer segments, products, and channels.

Develops and administers complex ETL and ELT data integration solutions using Microsoft Fabric, SQL Server, Lakehouses, Warehouses, pipelines, notebooks, and SSIS. Designs reliable data flows, consumption views, semantic datasets, and enterprise data models; troubleshoots data quality and pipeline issues; supports database administration, backup and recovery, reporting, deployment, and CI/CD. Collaborates with business, analytics, technical, vendor, and reporting teams to deliver secure, scalable, trusted data products.

Design, build, and operate Azure-based data pipelines and integrations. Consolidate data from multiple sources into centralized SQL systems, perform transformations and field mapping, and maintain data warehouse capabilities. Troubleshoot quality, integrity, latency, security, and reliability issues while applying governance, monitoring, and SLA practices. Collaborate with engineers, analysts, and stakeholders in Agile pods to deliver reusable, analytics-ready data assets.