Top Analysis Reporting Jobs in Greensboro, NC

Lead design and operationalization of enterprise data governance for insurance data across cloud and on-premises estates. Define operating models, stewardship, policies, data standards, quality frameworks, metadata/lineage, tooling, and MDM. Partner with business, actuarial, underwriting, claims, compliance, and tech teams to improve data trust, compliance, and reporting.

Lead enterprise data governance strategy and implementation. Partner with stakeholders to define data ownership, quality rules, metadata, and controls. Document requirements, processes, data dictionaries, and KPIs. Coordinate governance councils, audits, and vendor integrations, and embed governance into ETL and data integration pipelines to ensure compliance and data quality.

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.

Support TEA OnePlan and IDS initiatives by inventorying data systems, creating vendor-ready data maps, assessing data quality, and designing scalable Ed-Fi-aligned data integration strategies. Gather and document business and system requirements (Modern Requirements), process flows, UI mock-ups, and translate into functional requirements for vendor development. Support related IDS workstreams like LASO, GSA, and OneSystem.

Lead enterprise data architecture, migrations, and data services; define standards and roadmaps; oversee complex ETL and third-party integrations; deliver analytics, BI dashboards, and commercialization of AI analytics offerings; build the Data Strategy & Services organization and ensure continuity for legacy clients while partnering across Product, Engineering, Sales, and Customer Success.

The Insurance Product Analyst II supports state management for auto insurance products by conducting research, analyses, and executing product launches. Responsibilities include regulatory compliance, data analysis, and communication across teams.

Lead fraud analytics for application fraud detection: identify emerging patterns, design and test real-time defenses, balance risk and customer experience, build dashboards and metrics, and collaborate with Operations, Product, Data Science, and Engineering to reduce fraud losses and improve cardholder experience.

Support HRIS implementation by extracting, cleansing, validating, and preparing employee data for migration. Reconcile reports, fix duplicates and missing data, create Excel transformation files, maintain data quality, document work, and assist with testing and post-go-live support.

Lead process mining and improvement projects across business areas, develop dashboards and analyses (e.g., Celonis), apply industrial engineering practices, identify root causes, translate functional requirements to technical solutions, and drive customer experience optimizations.

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