Top Analysis Reporting Jobs in Greensboro, NC

Manage the end-to-end data issue lifecycle for North America: intake, triage, root cause analysis, remediation planning and execution oversight. Produce IMR reporting and dashboards, maintain audit-ready records, engage stakeholders, and improve IMR processes and tooling to strengthen data quality and controls.

Build, maintain, and improve AI-driven automations and data systems. Own Power BI dashboards and underlying pipelines (Python, SQL, DAX), manage complex margin/profit-share processes, create low-code AI automations (Claude, Zapier, Make), ensure data governance, and document/support solutions for company-wide use.

Manage the full data quality lifecycle for constituent records in Salesforce: deduplication, merges, data appends/enrichment, imports/exports, vendor management, audits, governance, reporting, staff training, and supervise a team focused on CRM data hygiene to support nonprofit fundraising operations.

Design, develop, and troubleshoot SAP reporting solutions, data marts, OLAP and dashboards. Translate business needs into BI solutions, follow data management processes, analyze trends, collaborate on database and architecture design, and evaluate future data delivery tools.

The Data Engineer will build and maintain scalable data pipelines, improve ETL processes, collaborate with AI/ML teams, and contribute to engineering culture.

Design and analyze experiments, measure campaign incrementality, identify customer segments and engagement opportunities, validate tracking and anomalies, surface actionable insights, and build scalable measurement infrastructure with cross-functional partners.

Design, build, and optimize scalable batch and streaming data pipelines. Model and process structured and unstructured data, ensure production reliability and observability, apply ML techniques for insight extraction, and drive data strategy while adopting modern tooling and IaC practices.

Work across data infrastructure and analytics: build and maintain dbt models, ingest and transform data, create dashboards and semantic layers in Power BI, validate AI-generated code, partner with stakeholders to deliver analyses and data products, and improve data governance and documentation.

Build and maintain revenue and customer-lifecycle reporting, author complex BigQuery SQL, develop segmentation and clustering models in BigQuery ML, perform entity resolution and data quality reconciliation, migrate and maintain Tableau dashboards, and deliver ad-hoc and recurring analyses to support Sales, Revenue, and cross-functional teams.

Build and own data platform infrastructure and scalable pipelines (ingestion, orchestration, transformation, delivery). Define governance, observability, and AI-first architecture. Optimize performance, ensure data quality, mentor engineers, and integrate AI-assisted tooling.