Top Senior Analysis Reporting Jobs in Des Moines, IA

The Lead Insurance Data Analyst will analyze data in healthcare, focusing on insurance billing processes, consolidate data from multiple sources, and provide actionable insights for department improvements.

The Senior Data Engineer will focus on Data Modeling, utilizing SQL, Snowflake, and Apache Airflow to develop efficient data models and deliver data products.

The Associate Director, Commerce Data leads data organization and usage to measure success and enhance business growth, collaborating across teams and ensuring data accuracy and reliability in reporting and forecasting.

Design, build, and maintain production data pipelines and tooling (CI/CD, testing, validation) using Snowflake, dbt, and orchestration tools. Model, transform, document, and optimize data to produce reliable curated datasets for analytics and solutions, enforce engineering best practices, and mentor teammates while ensuring scalability, observability, and data integrity.

Design and optimize BI semantic models and analytics workflows using PowerBI and Tabular Editor; build and transform large-scale datasets in BigQuery with dbt; implement CI/CD and deployment via GitHub and Azure DevOps; collaborate with stakeholders to deliver actionable visualizations and integrate Agentic AI into analytics pipelines.

Lead design and optimization of analytics products and Tableau dashboards, manage and tune reporting data pipelines (Redshift/ETL), implement performance best practices, collaborate cross-functionally, and drive automation and AI opportunities to improve reporting and analytics for healthcare customers.

Lead oversight of data management for assigned studies, manage external vendors, review and approve DM documentation, perform secondary UAT of EDC, implement RBQM oversight, and provide cross-functional input on protocols and study deliverables to ensure data quality and regulatory compliance.

Architect, build, and maintain scalable ELT data pipelines and analytics-ready data marts. Lead dbt modeling, ensure data quality, CI/CD, and documentation. Partner with stakeholders, mentor junior engineers, evaluate tooling (reverse ETL), and drive long-term data platform strategy.

Design, build, and maintain production data pipelines and the unified data model using Snowflake, dbt, and orchestration tools. Optimize, test, document, and monitor ELT workflows, enforce engineering best practices, mentor teammates, and deliver trustworthy data products for analytics and business decisions.

Lead the data organization to define data strategy, build scalable cloud-native pipelines, enable self-service analytics, drive AI/ML initiatives, and manage a multidisciplinary team to inform product, clinical, and business decisions.