Top Analysis Reporting Jobs in Des Moines, IA

The Data Analyst 2 will partner with various teams to optimize workforce strategies through data analysis, visualization, and reporting. Key responsibilities include extracting data, developing dashboards, and collaborating to inform business decisions.

Design, build, and operate resilient batch and streaming data pipelines. Own datasets end-to-end. Collaborate with data science teams and define data quality standards.

The Senior Manager, Partner Strategy & Analytics will lead analytics initiatives, define partner performance metrics, and drive strategic recommendations across partner programs to influence growth and productivity.

Lead analytics for Partner Sales Strategy: monitor KPIs, deliver data-driven insights, advise cross-functional leaders, support programs and reporting, perform root-cause analyses, and mentor junior analysts to drive growth and productivity.

The Revenue Operations Analyst will analyze performance metrics, conduct quantitative analysis, automate operations, and ensure data integrity to support revenue teams.

The Informatics Lead oversees Medicaid Prior Authorization analytics, ensuring regulatory compliance and operational excellence. They collaborate with teams, refine data solutions, mentor staff, and uphold data governance standards.

The Senior Manager, People Analytics will lead analytics initiatives to transform workforce data into strategic insights, manage complex projects, and communicate findings to executives, fostering a culture of data-driven decision-making throughout the organization.

The Director of Reporting and Data Management oversees data infrastructure for Workforce Management, establishing objectives, managing teams, ensuring data storytelling aligns with strategy, and leading predictive modeling efforts.

This role involves collaborating with stakeholders to translate business questions into data insights, developing SQL queries, and supporting AI-driven analytics workflows.

The Senior Data Engineer will develop and maintain scalable data pipelines, ensure quality standards, improve engineering practices, and engage with data teams to optimize operations.

The Manager of Data Engineering will lead the data engineering team, oversee data pipeline design and implementation, manage data governance, and ensure data quality while driving team professional growth.

The Lead Data Engineer will design and build scalable data pipelines on Databricks, develop ETL/ELT pipelines with PySpark, and mentor engineering teams for data transformation and analytics.

Design and develop scalable data pipelines using PySpark and Databricks, focusing on data ingestion, transformation, validation, and performance optimization.