Top Analysis Reporting Jobs in Richmond, VA

The Manager of Data Analysis leads a team to leverage analytics for improving customer experience, driving strategy, and implementing data models. Responsibilities include data mining, process improvement, and project lifecycle management, all within a collaborative environment.

Lead and mentor a data engineering team to design, develop, test, and support cloud-based big data and streaming solutions. Build full-stack data pipelines using Java/Scala/Python, RDBMS/NoSQL, Redshift/Snowflake, and cloud platforms. Collaborate with product managers, perform unit tests and code reviews, and promote engineering best practices and tech community engagement.

Lead data analysis and build/manage data solutions using scripting and open-source tools. Partner with business to create dashboards and drive insights. Manage data quality, metadata, lineage, governance, and collaborate with tech teams on security and access. Develop monitoring tools and support self-service data capabilities.

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.

Embed with the CRO to deliver GTM analytics and insights: write SQL and dbt models, build Looker and Salesforce dashboards, define and track revenue KPIs, forecast and model revenue, partner with GTM leaders and Data Engineering, lead analytics projects, and translate complex data into executive-ready recommendations to drive upsell and new-business growth.

Design, build, and maintain end-to-end data models and pipelines to support CX operations, compliance reporting, and customer insights. Create dashboards and metrics, enforce data quality and governance, automate recurring workflows, and partner with stakeholders and broader data teams to deliver self-serve analytics solutions.

Own end-to-end analytical lifecycle to develop and optimize business, risk, and growth strategies. Monitor portfolio and macro trends, build and interpret ML-driven models, lead cross-functional launches, mentor junior analysts, and build AI-assisted workflows to improve decisioning and measurement across products and geographies.

Build AI-augmented BI dashboards, semantic layers, and AI-ready metadata. Use AI-assisted tools to accelerate SQL and dashboard development, productionize ML outputs into BI, enforce data quality and governance, and present insights to business stakeholders including C-suite.

As a Healthcare Analyst II, you will analyze healthcare data to optimize strategies, conduct quantitative analysis, and provide insights for clinical interventions, partnering with cross-functional teams.

Lead design and build of ETL pipelines and Gold Layer tables in Databricks; develop semantic layers, data dictionaries, and AI-ready documentation; create dashboards and ad-hoc analyses to surface marketing and sales KPIs; partner with stakeholders to translate requirements into analytics-ready datasets and enable self-serve BI and agentic AI workflows.

Lead and mentor a data engineering team building scalable customer-focused data solutions. Hands-on technical ownership, architecture guidance, and delivery of data ingestion, transformation, and reporting. Advance AI-enabled development practices, set technical standards, and foster a collaborative, accountable engineering culture to improve speed, quality, and reliability.

Extract, transform, validate, and load client and Enverus data into MineralSoft using AI-enabled extraction tools and ETL processes. Configure mappings, run queries and reports, troubleshoot integrations with EnergyLink, and ensure data quality and completeness for internal and client use.