Top Senior Analysis Reporting Jobs in Richmond, VA

Lead Data Engineer responsible for designing, developing, testing, and supporting cloud-based data publication and transformation solutions. Collaborate across Agile teams to build distributed, real-time data pipelines and data warehousing (Redshift/Snowflake), perform unit tests and code reviews, mentor engineers, and adopt emerging technologies to deliver scalable data platforms.

Lead analytic work to build and maintain data solutions: mine diverse datasets, develop dashboards and BI tools, drive business insights, enforce data quality and governance, collaborate with tech teams on security and access, and use scripting and AWS to enable self-service analytics.

Lead analytics and strategy for retail and small business banking: identify opportunities, build pricing and credit risk models, support marketing, design targeted insights, test hypotheses, drive implementation, and partner with IT, Sales, Operations, and Finance to improve profitability and performance.

Lead design and implementation of data architecture for healthcare systems, influence stakeholders, mentor teams, ensure regulatory compliance, enable data integration and transformation, and apply AI techniques to improve healthcare operations and reporting.

Lead and grow a data engineering team that builds and operates ingestion, transformation, orchestration, and serving layers and a self-serve analytics substrate. Own data quality, observability, cost efficiency, SLAs, and engineering practices while partnering with Data Science, BIE, Analytics, and Product to deliver reliable, reusable data products.

Design, build, and maintain scalable dimensional data models, semantic layer, and production transformation pipelines. Collaborate with Data Engineering, Data Science, BI, DevOps, and Product to enable AI-ready data, ensure data quality and governance, support ML feature delivery, and coach analytics team members for robust, production-ready data products.

Lead and grow a team of analytics engineers while remaining hands-on with SQL, dbt, and Snowflake. Own roadmap and semantic layer development, build trusted, governed data products, partner with cross-functional stakeholders, champion data quality and observability, and hire and coach engineering talent to deliver scalable analytics and AI-ready foundations.

Lead end-to-end COGS and gross margin analysis for hardware and software products, model cost-saving scenarios, answer ambiguous executive questions, partner with data engineering/finance/product, build reliable datasets and analytical frameworks, and present recommendations to C-suite stakeholders.

Own SQL and dbt-based data modeling and data quality for clinical and claims datasets. Author and refactor dbt models/tests, triage DQ alerts, design monitors, optimize SQL performance, and collaborate with Data Engineering and stakeholders to ensure trusted production datasets.

Build and maintain governed Silver/Gold data models and semantic assets on Databricks. Translate stakeholder KPIs into testable, reusable transformations, apply enterprise modeling standards, enable domain self-service, ensure data sensitivity and governance, and review domain-contributed models for production readiness.

The Senior Data Analyst oversees performance reporting tools, automates data pipelines, conducts quantitative analyses, and communicates findings to various stakeholders.

Lead data analyst responsible for advanced analytics, real-time performance dashboards, network capacity modeling, and generating actionable insights for third-party service providers. Drives testing and pilots, analyzes stakeholder feedback, and serves as an internal analytics subject-matter expert to inform network strategy and operational improvements.

Build and scale the analytics foundation: own dbt projects and Snowflake warehouse, create trusted datasets and semantic layers for AI, build ELT pipelines from APIs, implement testing/observability and CI/CD, design reconciliation models, enable stakeholder self-service, and partner cross-functionally to drive data-driven decisions across GTM, Product, Finance, People, and Operations.