Top Data & Analytics Jobs in Richmond, VA

Leads a small analytics team while performing hands-on SQL analysis, healthcare claims and financial analysis, BI reporting, dashboard development, data governance, root-cause investigation, and process automation. Partners cross-functionally to identify revenue leakage, operational inefficiencies, data quality issues, and financial opportunities. Communicates data-driven recommendations to business and technical leadership and manages analytics priorities, quality review, coaching, and team development.

Lead enterprise metadata strategy, standards, governance, capture, curation, validation, lineage, and lifecycle management across data products and business assets. Partner with data governance, engineering, quality, analytics, modeling, and stewardship teams to improve data trust, discoverability, reuse, and AI readiness. Drive metadata automation, catalog synchronization, certification support, issue remediation, and stakeholder communications across a complex enterprise data environment.

Lead enterprise data quality practices by defining standards, rules, thresholds, scorecards, dashboards, and control frameworks. Partner with governance, engineering, product, and business teams to establish measurable requirements, embed controls across data products, monitor critical data assets, and resolve quality issues through root-cause analysis and remediation. Support AI-ready data initiatives through trusted datasets, lineage, certification, and governed usage while maintaining documentation and promoting continuous improvement.

Design and govern conceptual, logical, and physical enterprise data models supporting analytics, reporting, AI-ready datasets, and certified data products. Translate business requirements into scalable data structures across customer, product, payer, and territory domains. Establish modeling standards, review models against Common Data Model standards, maintain metadata and lineage accuracy, and resolve data gaps and inconsistencies. Collaborate with business, engineering, and technology stakeholders to provide modeling expertise and design guidance.

Lead SAP S/4HANA data migration activities: extract, map, transform, load, validate, and reconcile master and transactional data using BODS, Migration Cockpit, LSMW/BDC and HANA SQL. Support mock loads, cutover execution, defect remediation, and collaborate with functional owners to cleanse and correct source data.

Designs, develops, and maintains data pipelines, ETL processes, integrations, and complex data models. Supports analytics teams by sourcing and transforming business data for reporting and AI tools. Responsibilities include database modeling, SQL performance tuning, production support, data infrastructure development, requirements gathering, testing, deployment, stakeholder collaboration, and mentoring. The role works with relational and cloud data warehouses, data lakes, BI tools, and diverse data sources.

Owns the company’s BI platform and data strategy across clinical, operations, finance, and HR functions. Responsibilities include setting the analytics product roadmap, governing data definitions and PHI, managing platform architecture, building dbt models and dashboards, delivering healthcare quality and value-based-care analytics, deploying conversational AI, coordinating vendors and multi-team programs, and developing an analytics team. The role requires hands-on ownership of clinical data, EHR integrations, semantic modeling, governance, and executive reporting.

Builds and maintains analytical data foundations for lending, underwriting, pricing, originations, collections, and portfolio analytics. Develops reusable SQL assets, dimensional models, data marts, transformation workflows, reporting solutions, and business intelligence products using SQL, Python, dbt, Git, Snowflake, Power BI, and Sigma. Partners with technical teams, analysts, and business stakeholders to integrate data, standardize metrics, automate testing, and deliver reliable, documented, scalable analytical assets.

Perform Smart Sort activities to categorize, inventory, and classify customer records; determine whether records should be destroyed, retained, or integrated into inventory; and partner with the Records Manager on records lifecycle operations. The role requires expertise in records management, information governance, data classification, retention schedules, disposition protocols, and automated record sorting methodologies, along with strong analytical and detail-oriented problem-solving skills.

Build and maintain enterprise data pipelines and infrastructure supporting natural-language querying, semantic search, knowledge graphs, and GraphRAG for the SEC. Responsibilities include onboarding data sources, processing XBRL and financial filing data, managing metadata and lineage, validating data quality, monitoring pipeline health, resolving integration issues, and using AWS data services. The role also requires compliance with federal security standards and collaboration with the Data Architect.

Develop and maintain reports, dashboards, and business intelligence solutions to support decision-making. Consult with stakeholders, document business processes, administer business tools and systems, troubleshoot issues, and support solution implementation. Identify process-improvement and automation opportunities, manage change documentation, and respond to ad hoc data requests while collaborating across teams.

Build and operate large-scale data pipelines, web-scraping systems, and data-collection tools for AI datasets. Maintain analytical databases, optimize queries, troubleshoot pipeline and data-quality issues, manage containerized workloads across Kubernetes and Linux infrastructure, and support CI/CD workflows. The role also involves documenting technical processes, researching improvements, and developing scalable APIs in a fully remote environment.