Top Senior Data & Analytics Jobs in Richmond, VA

The Data & Analytics Leader will develop a multi-year roadmap to enhance data governance and analytics capabilities, while fostering a data-driven culture throughout ERAC.

Lead enterprise data architecture, governance, integration, and platform roadmap. Establish data models, lineage, cataloging, access controls (RBAC/ABAC/IAM), and M&A data integration while partnering with Finance, GTM, HR, IT, Security, Legal, and Product to ensure trusted, secure, and usable enterprise data.

Own design and implementation of a greenfield analytical data platform: ingesting PostgreSQL and Kafka streams, establishing governance, data lineage, quality, monitoring, and compliance-ready pipelines. Evaluate AWS-native tooling, Snowflake, and Databricks; produce RFCs and documentation; mentor junior engineers and ensure analytical systems remain downstream of transactional sources.

Lead cross-functional analytics to inform clinical and operational decisions: build Tableau dashboards, create dbt analytical models, analyze large healthcare datasets (claims, EHR, HIE) with SQL, respond to ad-hoc requests via JIRA, and collaborate with product and engineering to improve data capabilities.

The Senior Data Engineer will design and maintain scalable cloud-native data pipelines, develop APIs, implement advanced analytics, manage AI workflows, and enhance data operations collaboratively.

Design, build, and operate scalable cloud-native data pipelines and data lake/fabric architectures for Revenue Cycle Management. Implement ETL/ELT, integrate structured and unstructured sources and APIs, ensure data quality, lineage, and governance, and support AI/ML and analytics workloads with CI/CD and DevOps practices.

Lead a Salesforce data engineering team to design, deliver, and support Salesforce-to-Salesforce integrations and migrations, data modeling, ETL/transformations, automation, and observability. Manage hiring, performance, and career development; partner with stakeholders; adopt AI/LLM agent tooling to automate workflows and improve data quality; reduce technical debt and document systems and processes.

Perform actuarial analytics and forecasting to model financial and market trends, support value-based care contracting and implementation, ensure data integrity, develop metrics and forecasts, troubleshoot data issues, and advise leadership to inform strategic and operational decisions.

Builds and manages ETL processes and data pipelines in Azure Databricks using PySpark. Integrates data from multiple sources, tunes Spark and SQL for performance, troubleshoots pipeline failures, automates manual processes, and supports reporting and analytics to inform business decisions.

Lead analytics for Wealth Solutions: analyze client segmentation, revenue, and operational data; build models for capacity and workforce planning; produce insights and recommendations for senior leadership; partner with BI and Finance to improve advisor productivity, client experience, retention, and revenue growth; support strategic projects and translate complex data into clear presentations.

Support and develop BI applications for a client financial platform across environments. Build reports, analytics, and budgeting solutions (TM1), develop/tune Oracle SQL/PLSQL, deploy BI tooling, support UIs (low-code), follow Agile practices, and collaborate on integrations, security hardening, and operations.