Top Analysis Reporting Jobs in Milwaukee, WI

Leads end-to-end data and analytics architecture engagements, specializing in Microsoft Fabric platform design, implementation, modernization, migration, governance, integration, semantic models, reporting, performance, and cost optimization. Partners with clients and internal teams to translate business needs into scalable solutions, guides technical delivery, supports pre-sales pursuits, and mentors data professionals. The role is remote but requires travel four to six times annually and residence in an approved state.

Build data models, dashboards, reports, and visualizations using SQL, Power BI, Python, DAX, and Power Query. Analyze, clean, validate, and model data; troubleshoot systems; define alerts; identify process bottlenecks and automation opportunities; and improve data collection and reporting. Collaborate with business stakeholders, document projects, maintain data integrity, communicate insights, and train nontechnical teams on data usage.

Leads fraud analytics and fraud-vendor solution implementation across the enterprise. Identifies emerging fraud patterns, develops detection models, metrics, rules, scenarios, and controls, and applies statistical and data-mining techniques to mitigate risk. Partners with Fraud, Product, Technology, and business leaders, supports strategic initiatives, presents actionable insights, manages implementation, and serves as a subject matter expert in fraud data, modeling, governance, and criminal risk mitigation.

Senior Business Intelligence Engineer responsible for designing Account 360 Medallion Architecture, integrating enterprise and telemetry data, building predictive models and enrichment pipelines, and delivering actionable insights. The role uses Python, R, SQL, machine learning, NLP, and process mining to analyze device usage, customer workflows, and product friction. Responsibilities include rapid data-product deployment, stakeholder collaboration, sprint-based workload management, cross-training, technical debt reduction, and up to 15% travel.

Leads analysis of infrastructure, platform, operational, and service data to identify performance trends, risks, capacity constraints, and optimization opportunities. Develops reliability, availability, performance, and capacity KPIs; performs anomaly detection and root-cause analysis; and supports infrastructure modernization decisions. Builds scalable analytics solutions using SQL, Python, Alteryx, APIs, and Power BI while partnering with engineering, operations, SRE, architecture, and technology leadership teams.

Design and scale reliable data platforms, pipelines, Java microservices, APIs, and reporting infrastructure. Build data validation and reconciliation workflows, support distributed systems, improve pipeline performance and resiliency, and partner with engineering, analytics, and business teams. Contribute to cloud-native infrastructure, CI/CD, Docker, Kubernetes, dashboards, and self-service reporting modernization.

Leads CASL’s data analytics and business intelligence functions by integrating data across systems, developing SQL-based databases, reports, dashboards, and automated pipelines, and delivering actionable insights for institutional decision-making. Oversees SQL Server administration, data security, quality, integrity, and performance. Provides documentation and training while managing reporting projects, supporting leadership, and ensuring responsible handling of sensitive information.

Build and own customer-facing analyses, dashboards, and reusable reporting for ECP Insights. Conduct customer discovery, define reporting needs, write SQL and Python or PySpark in Databricks, contribute dbt models, validate accuracy, explain methodologies, and help prioritize the product roadmap. Collaborate with product, engineering, and customer-facing teams while handling HIPAA-protected health information.

Leads development of Navanta’s secure data backbone, including lakehouse architecture, bank-system ingestion, CDC pipelines, semantic modeling, data quality, reconciliation, observability, governance, and lineage. Partners with AI/ML, security, and platform teams to deliver reliable, queryable data products for financial institutions. Owns data contracts, access controls, regulatory data handling, pipeline SLAs, bank onboarding, and on-call reliability operations.

Designs, builds, and optimizes cloud data solutions using Microsoft Fabric and Azure. Develops data pipelines, Lakehouse architectures, ELT/ETL processes, data models, semantic models, and Power BI reporting. Partners with stakeholders to define requirements and technical designs, supports platform migrations, and implements data quality, governance, security, and monitoring practices. The role also contributes to AI and machine learning data initiatives and requires strong SQL, Python, PySpark, and modern cloud data engineering expertise.