Top Remote Analysis Reporting Jobs in Madison, WI

Lead clinical performance and outcomes reporting across facilities; analyze and distribute clinical data to support quality improvement, decision making, and resource utilization. Provide analytic leadership, train users, liaise with vendors, develop reporting processes, and support facility and enterprise quality and safety goals.

Design, build, and scale reliable batch and real-time data pipelines and warehouses. Partner with engineering, data science, and business teams to define data models, improve observability, optimize storage and querying, and evangelize data engineering best practices across the company.

Lead architecture and implementation of scalable data systems and pipelines from ingestion to delivery. Own ambiguous, high-impact integrations, improve data quality and reliability, adopt AI-augmented engineering, mentor engineers, and collaborate with Product, ML, and customer teams to ship production solutions.

Perform sponsorship valuations through research, data modeling, analysis, and client presentations. Maintain valuation database, surface insights, refine methodology, and support strategy projects to inform sponsorship proposals and renewals.

Design, build, and maintain scalable batch and streaming data pipelines and analytics-ready data models. Implement cloud (primarily AWS) data platform solutions, data ingestion, transformation, orchestration, and observability. Embed data quality, governance, security, and metadata/lineage practices. Partner with architecture, analytics, and application teams to enable self-service analytics, reporting, and downstream use cases while driving platform evolution and engineering best practices (CI/CD, testing, documentation).

Design, build, and maintain scalable, fault-tolerant streaming data architectures and real-time pipelines using Kafka, MSK, and Kinesis. Implement stream processing, monitoring, security, IaC, and CI/CD. Collaborate with data teams, provide technical leadership, and optimize latency, throughput, and cost for real-time analytics and downstream systems.

Serve as the bridge between business stakeholders and development for internal data initiatives. Own intake, discovery, and requirements documentation for analytics, BI, and reporting. Write user stories, acceptance criteria, data definitions, and reporting logic. Maintain a prioritized backlog, support stakeholder validation of prototypes, participate in agile ceremonies, and resolve requirement gaps and risks to ensure development can execute independently.

Serve as the primary bridge between IT and business partners to translate data needs into actionable data products (DaaP). Design enterprise data models, recommend technical solutions, oversee functional requirement translation to development-ready stories, ensure governance/security compliance, validate UAT, and communicate impact to stakeholders while supporting the ADI program.

Lead data engineering for a healthcare scheduling platform rebuild: map legacy multi-TB schema, design target schema, build translation layer (views/materialized views and write mappers), ensure data consistency during parallel systems, plan per-tenant cutover with verification and rollback, tune DB performance, instrument data quality/lineage/audit, and mentor engineers.

Perform hands-on data engineering to assess legacy sources, profile and cleanse data, design and run ETL/ELT migrations into Azure Government environments, validate and reconcile migrated data, implement data quality checks and basic governance, and prepare curated datasets for analytics (Power BI) while coordinating with application teams and producing contract deliverables.