Top Remote Analysis Reporting Jobs in Lincoln, NE

Lead ownership and evolution of a Microsoft Fabric-based data platform: design medallion/semantic architectures, build and optimize data pipelines, enable Power BI reporting, support SQL Server performance and API integrations, implement observability with Azure Log Analytics/KQL, and shape the data+AI roadmap.

Build and maintain data pipelines for network and operational telemetry, integrate DataMiner and other monitoring systems, create Power BI dashboards, configure monitoring metrics and alerts, automate reporting, analyze network performance and recovery events, and translate technical findings into actionable insights for technical and executive stakeholders.

Leads client measurement strategy, analytics audits, tracking implementations, QA, data modeling, attribution, CRO experimentation, privacy compliance, and migration analytics. Presents actionable findings to clients, partners across delivery teams, and helps grow the agency’s analytics practice through standardized processes, tooling, AI adoption, and sales support.

Own university data integrations from source discovery through validated, signed-off feeds. Build SQL queries and scheduled extracts, model data, support partner upgrades and migrations, translate institutional policies into accurate data feeds, and improve monitoring, documentation, and reusable integration patterns. Collaborate with registrars and database administrators while supporting a named set of university partners. The role requires deep experience with student information systems, including PeopleSoft, and occasional travel for partner onsite engagements.

Designs and maintains scalable data pipelines, warehouse models, and analytics solutions. Builds natural-language data interfaces using GenAI and LLM techniques, optimizes SQL, improves data quality and observability, and supports distributed data platforms on AWS or GCP. Partners with engineering, analytics, business, and product teams, contributes to shared codebases, establishes development standards, and participates in production on-call and incident response.

Leads data engineering, business intelligence, and analytics teams; oversees data pipelines, integration infrastructure, database architecture, CI/CD practices, and enterprise data platform strategy. Partners with business and technology stakeholders to define requirements, improve data capabilities, maintain Ubuntu-based services, and deliver reporting and KPIs to leadership. Responsible for team hiring, development, mentoring, operational health, and technical execution across analytics and data integration platforms.

Forecasts contact volume, capacity, and staffing for a virtual healthcare clinic. Monitors real-time queues, adherence, service levels, and intraday risks; combines multiple data sources to create staffing recommendations and reporting. Uses AI and LLM tools to test and improve forecasts, while accounting for clinician licensing constraints. Requires contact center WFM experience, strong Excel skills, analytical communication, and comfort working remotely with required equipment and connectivity.

Provides analytical and lifecycle support for U.S. Navy electromagnetic warfare, decoy, and SEWIP systems. Applies operations research, data science, logistics analysis, reliability and maintainability engineering, mathematical modeling, simulation, optimization, and what-if analysis to improve system readiness, operational availability, resource allocation, and lifecycle performance. Develops performance metrics, evaluates alternatives, analyzes complex datasets, and delivers recommendations and decision-support products to technical and program leadership.

Analyze healthcare and clinical operations data to deliver actionable customer insights, physician performance reporting, care-quality dashboards, and scalable BI solutions. The role requires SQL-based data transformation, dashboard development, collaboration with clinical, product, engineering, and client-facing teams, and clear communication of findings. The analyst will also use AI tools for query generation, data cleaning, pattern recognition, and analytical summaries.

Build and maintain data lakes, data warehouses, and modern data pipelines for a multi-tenant SaaS platform. Design end-to-end data processes, write pipeline and infrastructure code, conduct design reviews, optimize performance, monitor systems, support data governance, and troubleshoot scalability and security issues. Collaborate with technical and business stakeholders, mentor junior engineers, evaluate technologies, document platform architecture, automate testing, and participate in on-call rotation.