Top Senior Analysis Reporting Jobs in Omaha, NE

Develop and optimize enterprise Oracle SQL and PL/SQL solutions, including data models, database designs, APIs, ETL processes, batch jobs, and performance tuning. Collaborate with cross-functional teams to translate requirements into scalable implementations, support testing and CI/CD, troubleshoot production issues, and document solutions. Provide technical leadership, mentor engineers, participate in architecture and code reviews, and drive engineering best practices across data modernization initiatives.

Own board-grade analytics deliverables for client engagements by transforming Salesforce pipeline data and BI outputs into executive narratives, presentations, and reusable reporting templates. Analyze pipeline, funnel, and revenue performance; explain variance; write causal commentary; present findings to PE sponsors and executives; and train client teams to maintain deliverables independently.

Designs, builds, and operates production data pipelines on Databricks and Azure using Python, SQL, Spark, Delta Lake, dbt, and Dagster. Responsibilities include ingestion, medallion-layer transformations, dimensional modeling, ML datasets, data contracts, quality testing, governance, CI/CD, observability, performance tuning, troubleshooting, and on-call support. The role partners with architects, analysts, product owners, and business stakeholders to deliver reliable, reusable data products.

Build and maintain modern data-centric applications, pipelines, transformations, enrichment processes, provisioning layers, and user interfaces supporting clinical and operational healthcare processes. Analyze clinical data and report trends using cloud, big data, data science, and modern software development practices. Collaborate with Product, Platform, and Architecture teams, mentor Data Engineers, document solutions, manage source control, and research emerging technologies.

Senior individual-contributor analyst leading end-to-end, high-stakes analyses, designing dashboards and reporting, mentoring analysts, applying statistical methods and causal inference, partnering with analytics engineering to shape warehouse models, and translating findings for technical and non-technical stakeholders.

Responsible for administering, securing, tuning, migrating, and maintaining relational and non-relational databases across internal systems and client environments. The role includes capacity planning, backup and recovery, SQL optimization, performance monitoring, cloud database management, data pipeline maintenance, and troubleshooting. The administrator serves as a data management subject matter expert, supports deployment projects, recommends system improvements, presents metrics, and collaborates with development, managed services, partners, and customers.

Collaborate with business teams to define analytics needs, explore and analyze operational and financial data, build forecasts and regression models, and create dashboards and visualizations. Communicate insights to leaders, support decision-making, contribute to data modeling, metadata, quality remediation, and adhere to data governance, security, and privacy standards.

Designs and scales cloud-native data platforms and ingestion pipelines using AWS, Databricks, and Spark. Builds APIs, file-upload mechanisms, ETL/ELT workflows, and Lakehouse architectures; supports SQL Server data loading and legacy C# .NET processes. Partners with analytics, software engineering, architecture, and product teams to ensure data quality and availability for reporting and machine learning. Troubleshoots pipelines and applies governance, security, compliance, documentation, and reliability best practices.

Leads analytics and reporting for Microsoft’s Cloud Solutions Provider authorization ecosystem. Develops actionable insights, dashboards, data visualizations, and self-service reporting; improves data quality, governance, standardization, and efficiency. Partners with engineering, AI, operations, and compliance teams to automate workflows, identify risks, evaluate program outcomes, and recommend improvements. Presents findings to senior stakeholders and translates business needs into technical requirements and scalable analytical solutions.

Architects and scales enterprise data models, dimensional models, dbt transformation pipelines, semantic layers, and BI datasets. The role focuses on data quality, testing, observability, governance, metric standardization, documentation, performance optimization, and secure access controls. It partners with executives and cross-functional teams, leads analytics engineering initiatives, troubleshoots complex data issues, owns domain models, and mentors engineers while advancing the company’s analytics platform strategy.