Top Senior Data & Analytics Jobs in Richmond, VA

Design, build, and maintain scalable backend systems and data pipelines to generate point-of-care insights; collaborate with product and engineering stakeholders; mentor junior engineers; ensure solutions are secure, performant, maintainable, and support analytics and unified metrics collection.

Design, build, and deliver a global analytics platform: manage data collection and pipelines, develop visualizations and reports, create semantic models, tune performance, collaborate with IT and business stakeholders, and implement governance for analytics products.

Lead and scale companywide analytics for a DTC marketing business: own marketing measurement, financial forecasting, retention/LTV modeling, data architecture, reporting, and the analytics team. Set analytics strategy, oversee data engineering roadmap, build dashboards, apply statistical and ML methods, and translate insights into executive-level decisions.

Collects and organizes information for user manuals, training, installation guides, proposals, and reports. Edits functional descriptions and system specifications. Prepares and maintains systems, programming, and operations documentation and procedures. Maintains internal documentation library, supports financial/administrative tasks, coordinates documentation services, and works with Agile teams in a secure remote environment supporting government projects.

Lead revenue forecasting, planning, and executive reporting across new, renewal, and expansion revenue. Manage and grow a revenue insights team while owning pre-sales analytics, forecast methodology, capacity and quota planning, and performance narratives. Build pipeline and forecast reporting, track conversion/velocity metrics, surface risks early, and apply AI to improve forecasting, anomaly detection, and automated insights.

Build, maintain, and optimize cloud data pipelines and dbt models; design Airflow DAGs; implement dimensional models and BI dashboards; integrate healthcare data with HIPAA-compliant practices; contribute to RAG pipelines and MLOps workflows; review contractor code, monitor data quality, and document designs following governance standards.

The Director of Cloud FinOps will manage financial operations related to public cloud, optimize costs, and partner with various teams to maintain efficiency and profitability.

Design and implement enterprise data architectures and lakehouse/warehouse solutions using Microsoft Fabric, Databricks or similar platforms. Lead data modeling, ETL/ELT pipelines, cloud integration, CI/CD, and stakeholder-facing consulting engagements to deliver scalable, secure analytics systems.

The Senior Data Engineer will design and build data pipelines and infrastructure to support data science and business intelligence solutions, utilizing AWS services and streaming technologies.

Lead development and scaling of financial analytics: build data models, dashboards, and reporting; translate financial data into executive insights; embed predictive analytics; partner with Finance, IT, and business units to improve data quality, governance, forecasting, and automation.