Top Remote Data & Analytics Jobs in Richmond, VA

Leads development and maintenance of actuarial data marts, datasets, extracts, reports, and analytical solutions supporting claims analysis, IBNR reserving, forecasting, trend analysis, and financial reporting. Partners with actuarial, finance, medical economics, and data teams to validate and reconcile healthcare data, automate refreshes, ensure auditability, and improve data quality. Provides technical leadership, requirements expertise, recommendations, training, and direction to junior staff and business partners.

Research and fact-check thousands of hospitals for Forbes’ Top Hospitals 2027 list. Responsibilities include verifying hospital names, profiles, addresses, CMS facility IDs, and ratings; conducting online research and phone calls; maintaining accurate records; entering data; and potentially reporting and writing short healthcare articles.

Independently audit Forbes Top Hospitals 2027 rankings before publication by reviewing Python code against the methodology, validating Excel outputs, checking healthcare measure calculations, and assessing reproducibility. The role requires detailed process documentation, methodology-to-code traceability, testing evidence, precise recordkeeping, research, and clear communication of technical findings to diverse audiences.

Analyze, cleanse, transform, and integrate data from multiple sources; identify trends, correlations, anomalies, and KPIs; and build scalable Tableau dashboards, reports, and visualizations. Translate analytical findings into actionable recommendations for technical and business stakeholders. Maintain Tableau Prep workflows, support data governance, and collaborate with data engineers and IT professionals to improve data collection and retrieval.

Designs and leads production-grade batch, incremental, streaming, and real-time data pipelines across Microsoft Fabric and Azure. Builds Delta Lake medallion architectures, dimensional and Data Vault models, CDC and incremental-loading solutions, CI/CD automation, governance, security, observability, and data-quality controls. Supports migrations to Fabric, prepares governed data for AI and RAG workloads, and leads client-facing engineering workstreams, estimates, risk management, mentoring, and operational handover.

Analyze and maintain recruitment, onboarding, workforce, participant, and program-performance data for the NIH DataForce Service Program. Develop trackers, dashboards, reports, and briefing materials; monitor participant lifecycle activities; identify data-quality issues, risks, trends, and process improvements; and support recurring monthly and quarterly analyses. Collaborate with program managers, mentors, coordinators, and government stakeholders while protecting sensitive information and ensuring Section 508 accessibility compliance.

Lead the reverse-engineering and migration of legacy ETL pipelines from SAP BusinessObjects Data Services and JD Edwards into dbt and Databricks architectures. Build automated data validation, maintain SQL Server write-back mechanisms, collaborate with client stakeholders, and lead and mentor a small engineering team. The role requires hands-on expertise in SQL, Python, Spark, orchestration, cloud platforms, and legacy ERP and ETL migrations.

Lead enterprise data-source integrations across process historian, logistics, and procurement platforms. Build Databricks lakehouse Bronze ingestion pipelines and Silver normalization models, configure Fivetran and ODBC connectors, establish cross-system mappings, and validate data architectures with operations, procurement, and transportation stakeholders.

Designs, builds, tests, and maintains scalable data infrastructure and ETL/ELT pipelines for mission partners. Uses AWS Glue, Glue Catalog, and Step Functions to integrate, migrate, transform, and validate data. Develops data models, schemas, queries, and production-ready datasets while collaborating with analytics and business teams. The role may also support AI/ML pipelines, data governance, DevOps workflows, Databricks, and real-time streaming architectures.

Architects, builds, tests, and maintains scalable data infrastructure and ELT/ETL pipelines using AWS Glue, Glue Catalog, and Step Functions. Performs data modeling, SQL querying, data migration, schema optimization, validation, and data quality improvements. Partners with analytics and business teams to transform raw data into production-ready datasets. The role may also support AI/ML pipelines, governance, access controls, DevOps workflows, and real-time data architectures.

Own PushPress’s data platform, including ingestion, orchestration, cloud warehouse performance, governance, privacy, data quality, monitoring, and AI-ready data foundations. Build reliable pipelines integrating product, payment, and third-party data; establish data contracts, access controls, auditability, and semantic definitions; support real-time analytics and trustworthy reporting. Partner with Engineering, Data, and AI teams while maintaining infrastructure, incident response, documentation, and operational runbooks.

Build and own production data infrastructure for a healthcare AI platform. Responsibilities include REST API ingestion, Azure Event Hubs streaming into Databricks, Delta Lake medallion pipelines, entity resolution, semantic metrics, data-quality instrumentation, reconciliation, schema-drift handling, and troubleshooting source-to-warehouse discrepancies. The role requires strong Python and SQL skills, independent pipeline ownership, and experience with Databricks, Spark, PySpark, streaming, and healthcare-related data is a plus.

Own the Databricks enterprise data warehouse and BI solution, designing data models, ETL/ELT pipelines, stored procedures, semantic layers, and governed analytics. Lead healthcare data initiatives supporting value-based care metrics such as HCC, HEDIS, Stars, utilization, MLR, and capitation. Serve as BI product owner, manage roadmap and agile delivery, enforce data quality and HIPAA-aligned controls, and lead a small team while remaining hands-on.