Top Senior Analysis Reporting Jobs in Madison, WI

Leads data engineering strategy and mentors an analytics engineering team. Designs scalable ELT pipelines, warehouse integrations, data models, API ingestion workflows, and data quality frameworks using cloud and database technologies. Conducts exploratory analysis, supports dashboards and analytical solutions, monitors warehouse performance and costs, and ensures data governance, security, and compliance. Collaborates with data scientists, analysts, engineers, and business stakeholders to deliver healthcare analytics solutions.

Leads the architecture, implementation, and evolution of enterprise data platforms, including Master Data Management, data lakes, lakehouses, and cloud data services. Manages data engineers and developers, establishes engineering standards, oversees Azure-based integrations and pipelines, and owns data applications, databases, security, governance, and production support. The role also directs technical strategy, manages multiple initiatives, and communicates architecture and delivery plans to stakeholders.

Leads qualitative and quantitative market research to uncover customer, market, competitive, and healthcare insights. Designs and manages studies, analyzes data using statistical and AI-assisted tools, develops reports and dashboards, presents recommendations, maintains research quality, and coordinates external partners. Collaborates with product, engineering, sales, marketing, and customer success teams to influence product strategy, growth, innovation, and customer experience initiatives.

Lead the data engineering strategy and architecture for distributed pharmaceutical data systems. Design and scale pipelines, APIs, and data platforms while ensuring reliability, governance, quality, and PII/PHI protection. Drive technical decisions, improve developer efficiency, deliver business impact, influence cross-functional roadmaps, mentor engineers, communicate with executives, and promote organizational adoption of new technologies and processes.

Administers Oracle databases across development, test, staging, and production environments. Performs monitoring, maintenance, backups, recovery, patching, tuning, schema updates, indexing, troubleshooting, access control, encryption, auditing, and compliance remediation. Supports migrations, releases, environment synchronization, documentation, and collaboration with development and cybersecurity teams. Requires an active Top Secret clearance, database administration experience, relevant certifications, and strong Oracle, SQL, PL/SQL, and DoD security knowledge.

Design and own a unified data model for an AI-driven pipeline risk platform. Responsibilities include lakehouse and medallion architecture, geospatial modeling, entity resolution, ingestion patterns, governance, lineage, data quality, access controls, and traceability. Partner with data engineers, application engineers, and data scientists to implement schemas, pipelines, serving layers, and optimization strategies while maintaining clear architecture documentation.

Designs and maintains executive dashboards, reports, semantic models, and automated analytics solutions using Power BI. Defines enterprise KPIs, data standards, and business rules while integrating data from ERP, CRM, manufacturing, SQL, and cloud systems. Partners cross-functionally with senior leaders to deliver insights, improve data quality, support master data management, and enable scalable self-service analytics and data-driven decision-making.

Supports clinical data analysis, workflow improvement, solution requirements, project coordination, clinical content, dashboards, and customer engagement. Serves as a clinical subject matter expert, applying healthcare terminologies, data standards, SQL, Excel, and analytical tools to generate insights from EHR data. Collaborates with EHR vendors, pharmacies, payers, and internal teams on health IT initiatives and clinical solutions, including AI-enabled capabilities.

Lead the architecture, design, development, troubleshooting, and optimization of Snowflake data solutions for higher education clients. Conduct discovery and design workshops, assess existing environments, create enterprise data models and future-state architectures, develop ETL/ELT pipelines, implement security and data-quality controls, and optimize performance and costs. Serve as a client-facing technical advisor, translate business requirements into scalable solutions, lead technical workstreams, support business development, mentor teams, and travel periodically.

Leads analytics engineering and analytics-ready data architecture for government clients. Designs standardized data models, transformation logic, validation frameworks, and reusable integration patterns. Governs data quality, QA, backfills, and release processes while resolving complex data issues. Integrates web, email, social, survey, and client-system data to support dashboards, reporting, measurement, and insights. Advises stakeholders, influences enterprise standards, coordinates with product teams, and supports client-facing analytics workstreams.