Top Data & Analytics Jobs in Omaha, NE

Partner with Product, Design, Engineering, and Data to define KPIs and measurement for AI-powered features, guide instrumentation, design and evaluate experiments, build dbt models, create dashboards, and influence product analytics standards and long-term strategy.

Perform part-time quality audits and evaluations of task outputs, define and refine quality benchmarks and scoring rubrics, analyze audit results to produce actionable insights and reports, and recommend process improvements to raise output quality.

Develop and lead healthcare analytics and BI solutions for HIS products: design, code, and deliver enterprise-scale applications and dashboards, work with AWS data services and BI tools, support product development and troubleshoot reporting issues for global customers.

The Lead Risk Analytics Data Scientist will develop risk pricing, design data models, automate workflows, and communicate insights to leadership. Responsibilities include owning the risk narrative, building analytics foundations, and utilizing AI to enhance efficiency.

Lead Data Engineer responsible for defining architecture, engineering standards, and best practices for the enterprise data platform, collaborating with distributed teams for modernization and scalability.

Assist in collecting, cleansing, and analyzing datasets to produce actionable insights, reports, and dashboards for informed business decisions.

Lead architecture, operation, and continuous improvement of cloud-native, enterprise-scale data platforms (Snowflake, cloud storage, streaming). Translate requirements into roadmaps, design and optimize data warehouses and lakes, automate operations with Python and IaC, mentor engineers, and deliver managed services across multiple client accounts while driving reliability, security, and performance.

Designs, builds, and maintains scalable batch and streaming data pipelines, ETL/ELT workflows, data models, and Python transformations. Writes optimized SQL, monitors pipeline reliability, troubleshoots failures, implements data-quality validation, and supports security and governance practices. Collaborates with engineers, analysts, stakeholders, and clients to define data contracts, improve platforms, document lineage, and deliver reliable analytics data.

Build and maintain Rayda’s data warehouse, analytics infrastructure, data models, transformation layers, pipelines, and workflows. Integrate product, billing, and customer interaction data from multiple platforms, improve data quality and governance, and create reliable datasets and analytical models. Enable self-service analytics and collaborate with Product, Growth, Commercial, and leadership teams to uncover usage patterns, churn risks, and expansion opportunities.

Leads and develops an analytics engineering team that builds data pipelines, analytical models, reporting, and scalable data infrastructure. Partners with Product, Engineering, Growth, and Operations to deliver reliable, actionable data. Establishes governance, quality, testing, documentation, and modeling standards while prioritizing analytics projects and communicating with stakeholders.