Top Remote Analysis Reporting Jobs in Raleigh, NC

The Data Analyst will build key data models and metrics for decision-making, partner with stakeholders for analytical insights, create datasets for self-service reporting, and ensure data reliability through quality checks.

The Lead Data Platform Engineer will design and build Virtuous's data platform, ensuring it is secure, scalable, and AI-ready. Responsibilities include architecting access controls, optimizing performance, and enabling self-service analytics while maintaining governance and compliance standards.

As a Salesforce Technical Architect focused on Data & AI, you'll design and implement solutions using Salesforce Data 360, oversee technical projects, collaborate with various stakeholders, and mentor junior staff to drive AI innovations.

Oversee technical SEO work for clients, manage teams, define objectives and measure success against KPIs, while mentoring team members and ensuring high-quality delivery.

Develop and maintain Epic Healthy Planet registries and analytics solutions: gather requirements, profile Epic source data, build rules/metrics/dashboards, provide ad-hoc analysis, support end users, document solutions, and mentor users.

The Sr. FWA Analyst identifies fraud, waste, and abuse in medical billing through data analysis, supporting engineering and data science teams with validation and tuning of detection algorithms.

The Business Intelligence / Data Analyst will optimize the data reporting pipeline using Google Big Query and Omni, work with product management, implement reports, and conduct ongoing maintenance.

Lead enterprise data strategy and governance to establish semantic architecture, metadata, lineage, stewardship, and standards enabling trusted data for AI, analytics, and operations. Define operating model, policies, reference architectures, and roadmaps while partnering with Legal, Compliance, Security, Technology, and business leaders to ensure regulatory compliance and enterprise-wide adoption.

Design, build, and maintain scalable ETL/ELT data pipelines on Databricks and AWS S3; manage large geospatial and temporal datasets; productionize ML models; implement data validation, testing, and monitoring; optimize storage and processing; document workflows; collaborate cross-functionally.

The DMS Data Engineer is responsible for analyzing raw data, building data systems and pipelines, conducting complex data analyses, and collaborating on projects to enhance data quality and reliability.