Top Senior Data & Analytics Jobs in Greensboro, NC

Lead data management and quality efforts, consult with stakeholders and vendors, design processes and solutions, perform root-cause analysis of complex data errors, implement improvements, integrate technologies, validate deliverables, and present recommendations to senior management to enable AI-ready data and BI solutions.

Build and maintain scalable ETL/data pipelines and internal frameworks to support ML and product teams. Drive architecture, observability, data quality, and engineering best practices across AI/ML workflows and prompt-engineering pipelines.

Build governed gold-layer data models and a single-source metrics layer in Snowflake (dbt); create and optimize dashboards in enterprise BI tools; use AI coding agents and AI-assisted tooling to accelerate development; ensure data quality, governance, and consistency; collaborate with data engineering and stakeholders to deliver trusted analytics for internal and client-facing use.

Client-facing BI consultant responsible for end-to-end delivery of TARGIT-based analytics: requirements gathering, prototyping, backend work, dashboards, training, deployment, optimization, and customer engagement.

Lead enterprise data strategy and governance, build AI-ready data infrastructure and BI systems, own SharePoint platform, partner cross-functionally to ensure data quality, access, compliance, and user adoption.

Design and maintain enterprise data architecture across AWS and Azure, lead Snowflake data warehouse strategy, ensure data governance and HIPAA compliance, enable BI and AI/ML pipelines, collaborate with engineers and stakeholders, and recommend modern data technologies and standards.

Design and implement scalable Azure-based data architectures and analytics solutions, lead delivery teams, support pre-sales, drive DevOps/CI-CD, mentor junior staff, define data strategy, governance, migrations, and oversee project delivery and backlog management.

Design, build, and maintain scalable data pipelines, data models, ETL/ELT, and BI solutions. Collaborate with data scientists and stakeholders to improve data quality, accessibility, and PHI security. Develop and document workflows, optimize processing/storage, support data warehouse and visualization, and adopt AI tools to drive data-informed outcomes.

Build and maintain scalable monitoring solutions and dashboards to track production, campaign, and operational data. Analyze large-scale datasets to detect anomalies, perform root-cause investigations with Engineering and Production Operations, and deliver actionable insights to improve platform reliability and operational efficiency.

Lead analytics work across operations, finance, clinical quality, and BD. Build and maintain BI tables and dashboards, ensure metric accuracy, run operational and growth analyses, support financial forecasting and partner reporting, and deliver ad-hoc analyses to improve efficiency, patient experience, and strategic decisions.