Top Analysis Reporting Jobs in Richmond, VA

Lead design, build, and support of cloud-based ETL, data warehousing, and reporting solutions. Develop/optimize ETL pipelines, data models, and queries; deploy containerized services on Kubernetes; automate workflows; mentor teammates; collaborate with architects, data scientists, and stakeholders to deliver scalable analytics and reporting products.

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.

The Lead Partner Success Implementation Engineer drives partner success through strategic implementation, technical guidance, and collaboration, ensuring optimal platform usage and partner enablement.

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

Lead and expand the company's BI and analytics capabilities: set data strategy with senior leadership, manage analytics pipeline and BI stack, implement data governance, mentor and grow BI and data engineering teams, partner cross-functionally to drive data-informed decisions, and manage vendors and processes for scalability.

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 Data Scientist will enhance statistical models for forecasting, analyze datasets for operational planning, and communicate insights to stakeholders.

The Data Engineer will develop and maintain data pipelines, build data models, ensure data quality, and support cross-functional teams while improving internal data platform infrastructure and documentation.