Top Remote Analysis Reporting Jobs in Richmond, VA

Support national community lending initiatives by developing ROI dashboards, analyzing event and CRM data, coordinating events and partners, enabling sales teams, managing budgets/contracts, and producing program performance insights to scale community outreach and homeownership programs.

Design, build, and maintain scalable ETL/ELT pipelines and Lakehouse solutions; ingest and transform diverse data formats; optimize Databricks and SQL Server environments; implement data quality, lineage, and governance; support batch and streaming ingestion; collaborate with analysts and stakeholders to enable analytics (fraud/anomaly detection, financial oversight); troubleshoot and improve pipelines. Candidates must be willing to undergo a U.S. government background investigation.

Partner with Product, Design, Engineering, and Data to define KPIs and measurement for AI-powered features, guide instrumentation, design and evaluate experiments, build dbt models, create dashboards, and influence product analytics standards and long-term strategy.

The Director of Data and Enterprise Applications oversees the architecture, development, and support of business applications and data platforms, driving digital transformation and ensuring data integrity and accessibility.

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.

Partner with hospitality leadership across 40+ amphitheaters to deliver BI and analytics: build dashboards, inform pricing and concessions strategy, analyze labor and cost, support data integrity, run experiments, and act as a live-music subject matter expert to drive operational improvements and client relationships.

Own end-to-end data pipelines for multiple clients: extract, clean, transform, model and visualize data. Build dashboards and automated workflows, apply AI where useful, and present actionable insights to non-technical stakeholders.

Lead analytics and data science initiatives to drive measurable business outcomes across various functions, including Underwriting and Claims. Oversee the full analytics lifecycle, foster stakeholder engagement, and mentor junior team members.

Early member of the Data & Analytics team responsible for end-to-end analyses and data products. Build and maintain dbt models, semantic layers, and dashboards (Power BI). Partner with Finance, Merchandising, Marketing, Operations and others; own metric definitions, validate AI-generated SQL/dbt/Python, investigate data discrepancies, and help evolve Snowflake-based data infrastructure and governance.

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.