Top Remote Analysis Reporting Jobs in Lincoln, NE

Own Silver and Gold medallion-layer modeling and semantic layer governance using dbt and SQL. Improve warehouse performance and cost, standardize BI tooling, collaborate with stakeholders to produce trusted metrics, troubleshoot data quality, and evolve analytics platform.

Own implementation, maintenance, and optimization of client eligibility and claims data feeds. Analyze feed performance, troubleshoot discrepancies, produce error reports, test integrations with external partners, and improve internal tools, documentation, and processes to increase automation and reliability.

Owner of the analytics foundation: design and maintain BigQuery/dbt models, pipelines, and Looker Studio reporting; build AI workflows and web apps on GCP; integrate marketing, e-commerce, and fulfillment data; ensure GCP ops, security, and reliability; use AI-assisted tools daily and collaborate with business and client stakeholders.

Manage analytical service operations by overseeing a team, designing software for data mining, developing statistical models, and generating insights for marketing outcomes. Provide training and mentorship to direct reports.

Gather and document business and functional requirements, analyze processes, recommend improvements, produce BRDs/FRDs/user stories and process maps, support solution design, UAT, testing and deployment, produce reports/dashboards, monitor project progress, and support change management and stakeholder communication.

Lead Salesforce data migration and quality activities for a Department of Veterans Affairs modernization program. Analyze SQL Server data, create source-to-target mappings, execute ETL and Salesforce loading, validate and reconcile records, implement data quality controls, and develop migration and application test plans. Track defects, support automated monitoring and testing, collaborate with architects, developers, stakeholders, and provide migration status, risk, and quality updates.

Design and build petabyte-scale multimodal data pipelines and infrastructure (text, audio, images, video). Own and maintain systems like Spark, Ray, and vector databases, partner with pre/post-training teams to improve data recipes through experimentation, and support large-scale dataset storage and processing for AI model training.

Partner with sales leadership to define business requirements, design end-to-end analytics solutions (data models, semantic layers, dashboards), build scalable Power BI/Microsoft Fabric reporting, translate data into executive-ready insights, drive automation and standardization, mentor analysts, and influence business decisions with data-driven recommendations.

Leads business intelligence, KPI reporting, and performance measurement for Part D risk adjustment programs. Defines business rules, metrics, reporting requirements, and analytic specifications; translates business needs into dashboards, recurring reports, and curated datasets. Partners with IT and enterprise data teams on scalable analytics, automation, governance, and controls. Validates BI outputs and communicates complex data insights to senior and executive leadership.

Designs, builds, maintains, and optimizes scalable data pipelines and ETL/ELT workflows using Azure Databricks, SAS, SSIS, SQL, Python, Spark, and Azure services. Integrates internal and external data sources, improves pipeline performance and reliability, troubleshoots processing issues, supports Big Data solutions, and partners with engineering, product management, SRE, analytics, and cross-functional teams to deliver enterprise data platforms.

Own GTM reporting and analytics across Salesforce, warehouse systems, Tableau, and Excel. Build trusted dashboards, define metrics, investigate data quality issues, and lead analysis for pipeline, forecasting, territory design, capacity planning, productivity, and resource allocation. Partner with GTM, CRM, Data, and Systems stakeholders to improve reporting architecture and support leadership decisions. Use AI tools to automate analysis and develop internal analytics workflows.

Design and manage financial systems for accurate cashback calculations, build and maintain reconciliation processes, ensure data integrity for yield-bearing instruments, collaborate with compliance, and partner with cross-functional teams to improve financial system efficiency.