Top Remote Analysis Reporting Jobs in Lincoln, NE

Transform complex data into actionable insights, develop reports and dashboards, ensure data quality, and manage client relationships to meet their data needs.

Lead and scale the data analytics organization, guiding teams, driving product analytics strategy, and integrating AI to enhance data-driven decision-making across the company.

The Product Data Analyst leads data collection and analysis to inform product strategy, collaborates across teams, and ensures data integrity for decision-making in product management.

The Lead Implementation Specialist is responsible for data integration, reporting, and visualization, ensuring compliance, facilitating client support, mentoring, and driving continuous improvement in data processes.

Lead design and delivery of large-scale data pipelines and warehouse systems. Define technical strategy, enforce data governance, improve developer efficiency, mentor engineers, and align data engineering efforts with business goals to enable analytics and ML at scale.

The Data & Analytics Leader will develop a multi-year roadmap to enhance data governance and analytics capabilities, while fostering a data-driven culture throughout ERAC.

The Bioinformatics Support Analyst provides operational and analytical support for biomedical informatics applications, ensuring data quality, system performance, and workflow optimization while collaborating with engineering and scientific teams.

The GIT Technical Specialist delivers GIS analysis and data validation for NG911 and public safety, develops workflows, and mentors junior staff, supporting multiple projects.

Lead enterprise analytics strategy and roadmap, consolidate analytics teams, deliver data products and governance, scale advanced analytics and MLOps, partner with IT and business leaders to drive data-driven decision-making and measurable financial impact.

Lead design and scaling of enterprise data architecture and pipelines. Build and maintain ETL/ELT and CDC/streaming workflows, improve data quality and observability, own schema and warehouse modeling, implement governance (RBAC), and provide cross-functional technical leadership to enable trusted, scalable data for analytics and product teams.