Top Entry Level Data & Analytics Jobs in Richmond, VA

Collects, validates, cleanses, and analyzes student enrollment and financial aid data for college and university partners. Responsibilities include sending data requests, resolving data discrepancies, preparing data for forecasting models, creating charts and graphs, developing partner reports, and preparing PowerPoint presentations. The role collaborates with senior analysts and partners and may involve intermittent travel to college campuses.

Develop and customize Data Warehouse reports using Excel by writing queries to connect to Oracle. Build and optimize SQL queries, understand Oracle database structures and tables, and tailor report outputs. Familiarity with how Excel generates reports from Oracle is required. Cognos Impromptu experience is a strong plus. Position requires 100% onsite relocation and candidates must be U.S. citizens or green card holders.

Analyze business processes, systems, and datasets to define requirements, develop data models, implement governance and quality practices, and produce actionable insights. The role includes data profiling, ETL and data wrangling, statistical analysis, visualization, reporting, and stakeholder communication. Data Analysts collaborate with engineers, architects, scientists, product owners, and clients to solve complex business problems and support informed decision-making.

Reviews, develops, validates, and refines dashboards, reports, visualizations, calculations, data sources, KPIs, and analytical workflows across BI platforms. The role documents findings, provides structured feedback, troubleshoots reporting accuracy, and evaluates AI-powered agents and workplace connectors used in analytics processes.

Monitors healthcare data workflows, validates and reconciles files, troubleshoots database and data-integration issues, performs quality audits, maintains backups, and supports operational reporting. The analyst documents procedures, communicates data discrepancies and resolutions, assists with month-end processes, and helps improve standardized workflows while protecting confidential client information.

Coordinates data and process activities for a Managed Services Center, including ServiceNow CMDB reconciliation, data entry and validation, contract updates, quality assurance, task tracking, documentation, auditing, and business continuity support. Collaborates with internal teams and vendors to maintain accurate records, resolve discrepancies, and support ServiceNow operations. The role is remote and highly keyboard-intensive.

Analyzes supplier deal performance, revenue opportunities, forecasts, and commercial risks for global travel partnerships. Supports supplier negotiations, models deal structures, develops strategic reporting and optimization plans, and translates complex data into actionable recommendations for leadership, Sales, Pricing, and Client Management. The role requires strong analytical, commercial, communication, stakeholder engagement, and strategic thinking skills.

Build and maintain production data ingestion pipelines, transformation models, warehouses, and schemas for PerfectServe’s data platform. Deploy reliable, tested pipelines using idempotency and data-quality checks, apply dimensional and medallion modeling, participate in design reviews, and document owned pipelines and runbooks. The role requires SQL, programming experience, dbt or similar transformation tools, cloud data warehouse experience, ELT orchestration, AWS knowledge, and a strong data-testing mindset.

Analyzes institutional data, surveys, student success metrics, enrollment trends, academic information, and KPIs. Prepares internal and external reports, data visualizations, statistical analyses, and presentations supporting university planning, accreditation, strategic initiatives, grants, and program reviews. The role also provides survey design and data-analysis consulting to university departments and ensures data integrity.

Own end-to-end data workflows, including ingestion, storage, orchestration, transformation, validation, and delivery. Build ETL/ELT pipelines, manage cloud data platforms and transfers, optimize data models and queries, maintain data quality monitoring, troubleshoot production issues, and document data flows. Collaborate with technical and nontechnical teams to investigate discrepancies, support enterprise datasets, and apply secure data-handling practices.