Top Analysis Reporting Jobs in Des Moines, IA

The Senior Data Analyst will provide high-quality analytics and insights for business strategies, automate reporting, and collaborate across teams to transform data into actionable insights.

Manage analytical service operations by overseeing a team, designing software for data mining, developing statistical models, and generating insights for marketing outcomes. Provide training and mentorship to direct reports.

Lead the evolution of data platform by designing scalable pipelines, improving data processes, mentoring teams, and modernizing data architecture.

The Sr. Operations Analytics Manager will enhance billing and account efficiency, analyze complex data, and provide actionable insights to improve financial performance and customer service.

Maintain and improve eligibility and claims data feeds, analyze feed performance and errors, troubleshoot discrepancies, work with external feed providers to map and test integrations, and help improve internal tools, documentation, and processes.

The Senior Data Engineer II will design and maintain scalable data pipelines, collaborate with teams on machine learning workflows, and ensure data accessibility across systems.

The Analytics Engineer will manage BI modeling, create dashboards, ensure data quality, and collaborate with customers and teams for reporting needs.

Lead Pager Health’s enterprise data and reporting strategy, build a centralized data and reporting shared services function, own internal dashboards and client-facing analytics, partner with Product and Engineering on data architecture and governance, mentor data teams, prioritize and deliver data initiatives, and drive continuous improvement in tooling, automation, and data storytelling to support growth, efficiency, and client outcomes.

The Senior Data Engineer will architect, build, and maintain scalable data pipelines and infrastructure, mentor junior engineers, and collaborate on data solutions for Openly's insurance platform.

The Senior Data Engineer will own and evolve data pipelines, collaborate with teams for data models and pipelines, optimize ETL processes, and implement data storage solutions.