Top Data & Analytics Jobs in Greensboro, NC

Build network capacity and demand forecasts across 50 states, support clinician recruitment and retention analytics, measure clinical and scheduling outcomes, and design experiments with Product and Engineering. Develop governed data models, KPI definitions, and AI-powered analytics infrastructure. Serve as the primary analytics partner for Network leadership by translating complex, multi-source data into actionable recommendations and presenting insights to technical and executive audiences.

Develop dashboards, reporting, and analytics solutions for business teams; monitor performance trends, data quality, risks, and key metrics; investigate complex questions; support A/B testing and instrumentation; and communicate actionable insights to technical and non-technical stakeholders. The role also requires expertise in profit drivers, unit economics, campaign and funnel performance, and the company’s analytics infrastructure.

Leads the database engineering and architecture function supporting medical imaging platforms. Responsibilities include managing and developing database engineers and architects, defining scalable and secure database strategies, overseeing reliability, capacity planning, backup and disaster recovery, enforcing HIPAA and healthcare interoperability compliance, evaluating database technologies, and leading migrations and modernization across cloud, on-premises, and hybrid environments.

Defines and documents client business and technical requirements for analytics solutions, collaborates with developers on design and testing, and delivers data ingestion, reporting, dashboards, business intelligence, data warehousing, and advanced AI/ML applications. Partners with delivery and account management teams to ensure customer satisfaction, provide analytics consulting, and recommend appropriate cloud and BI technologies.

Build and maintain branch network performance reporting, dashboards, semantic models, and analytical datasets using SQL and Alteryx. Translate banker, branch, market, and enterprise data into actionable insights for senior leaders. Lead analytical projects, manage timelines, communicate executive-ready findings, improve reporting processes, and mentor junior analysts. Partner with Distribution and Consumer Bank leadership in a hybrid, primarily onsite environment.

Research and monitor political news, government sources, candidates, officeholders, and elections. Update Ballotpedia articles and databases, verify data accuracy, conduct jurisdictional research, write and proofread neutral content, maintain tracking spreadsheets, and collaborate across teams. The role requires strong political knowledge, organization, communication, project management, attention to detail, and flexibility for occasional evening and weekend work.

Data Engineer II will modernize BlueLabs’ data platform by leading Kimball dimensional modeling and legacy warehouse migrations, building reliable production data pipelines, and enforcing data quality standards. The role requires advanced SQL, Python, and dbt expertise, hands-on Snowflake and Redshift experience, and ownership of testing, documentation, observability, and scalable architecture. The engineer will collaborate cross-functionally, guide Data Engineer I team members, contribute to architectural decisions, and translate business logic into maintainable, cloud-agnostic data layers.

Own analytics and reporting solutions for acquisitions, product launches, and other complex business events. Translate business changes into data models, system updates, processes, and reporting definitions. Coordinate Data Engineering, Analytics, Data Science, and Data Governance teams; lead cross-functional execution and establish a Business Intelligence Council. Partner across GTM, Finance, Product, IT, and other functions to reconcile metrics, clarify ownership, and maintain business visibility.

Develop and maintain Python scripts and automated workflows for NLM metadata management. Integrate Alma, OCLC, and other systems through APIs and batch exchanges; process, transform, validate, reconcile, and analyze bibliographic and authority metadata in formats including MARC, XML, JSON, and CSV. Implement logging, exception handling, reporting, and documentation while supporting workflow testing, systems integration, and automation improvements.

Lead enterprise data engineering standards, governed pipelines, data contracts, observability, quality controls, lineage, testing, and compliant data delivery. Partner with governance, privacy, architecture, modeling, and platform teams to ensure reliable, traceable, protected data products. Monitor operational performance, automate deployment and validation, and resolve pipeline and data reliability issues across complex enterprise environments.