Top Analysis Reporting Jobs in Omaha, NE

The Data Engineer will enhance the Enterprise Data Warehouse, modernizing ETL processes, optimizing data transformations, ensuring data quality, and providing production support while collaborating with cross-functional teams.

As a Lead Data Engineer, you'll optimize data workflows, manage data engineering projects, mentor junior engineers, and ensure robust data solutions meet business needs.

Design and maintain cloud data lake architecture, build ingestion and transformation pipelines from SaaS sources, enable analytics and BI (Tableau/Looker), enforce governance, and lead technical direction across teams.

As the Director of Global Support Analytics, you'll oversee analytics and process optimization to enhance customer support, integrating various data sources and establishing KPIs for operational excellence.

As a Senior BI Data Analyst, you'll analyze complex datasets, build SQL queries, develop predictive models, and create dashboards to drive insights and recommendations.

The Senior Business Analyst will provide data-driven insights to enhance the performance of the Support organization, focusing on analytics, dashboard creation, and operational improvements.

Collect, analyze, and interpret complex data; build and maintain data systems and models; create visualizations, reports, and dashboards; collaborate with cross-functional teams to inform business decisions.

Design, build, and maintain scalable Databricks-based data pipelines; lead migration/rehydration of ~500 PowerBI reports; implement CI/CD for data assets; optimize ETL/ELT and establish DevOps/versioning/testing best practices.

Design, build, and operate scalable batch and streaming data pipelines; partner with customer and product teams to implement health system integrations; improve monitoring, tooling, and data accessibility; serve as a dataset and tooling subject matter expert.

Lead and mentor a data engineering team to design and operate scalable ETL/ELT pipelines and Snowflake data warehouse solutions using Python, DBT, Matillion, and AI tools; establish standards, ensure data quality and governance, and collaborate with analytics, product, and BI stakeholders to deliver production-ready data platforms.