Top Senior Data & Analytics Jobs in Richmond, VA

Lead development of cloud data platforms and end-to-end data pipelines using AWS/Snowflake and big-data technologies (Spark, Hive, Iceberg). Automate builds and deployments with Bash/Python shell scripting, apply CI/CD and Medallion Architecture, perform data modeling and warehousing, and collaborate across teams. Pharma/AbbVie experience preferred.

Provide hands-on support for procurement and finance systems: implement and optimize ERP/source-to-pay platforms, maintain master data, validate reporting, troubleshoot issues, support system upgrades, automation, BI/dashboard development, and change management to ensure data integrity and operational efficiency across finance and procurement.

Owner of cross-functional analytics projects: build and maintain dbt models, write advanced BigQuery SQL, create BI dashboards (Omni/Power BI), monitor data quality, define metrics, enable stakeholder decisions, and use AI tools to accelerate analysis and QA.

The Senior Data Engineer will design and implement lakehouse architectures, optimize ClickHouse deployments, develop ETL/ELT pipelines, and create data models to support analytical and operational functions.

Own slide-grade analytics for PE and executive audiences by transforming Salesforce and BI outputs into polished board packs, causal commentary, reusable templates, and executive narratives. Attribute pipeline variance, produce funnel and revenue analytics, train client teams, and ensure deliverables are modular, PE-ready, and maintainable across engagements.

Client-facing Analytics Manager who architects large-scale digital analytics (GA4/Adobe), audits implementations, builds measurement frameworks, and leads GEO (Generative Engine Optimization) test & learn programs. Uses AI tools (Claude) to automate workflows, mentor teammates, manage projects, and translate data into strategic client recommendations.

Lead scaling of Arbital's AWS/Databricks lakehouse and Spark pipelines, implement actuarial healthcare calculations, own Airflow orchestration and CI/CD, ensure data quality and HIPAA-compliant PHI handling, partner with data scientists to deploy ML models, and set platform architecture and engineering standards.

Design, build, and maintain scalable backend systems and data pipelines to generate point-of-care insights; collaborate with product and engineering stakeholders; mentor junior engineers; ensure solutions are secure, performant, maintainable, and support analytics and unified metrics collection.

Design, build, and deliver a global analytics platform: manage data collection and pipelines, develop visualizations and reports, create semantic models, tune performance, collaborate with IT and business stakeholders, and implement governance for analytics products.

Lead and scale companywide analytics for a DTC marketing business: own marketing measurement, financial forecasting, retention/LTV modeling, data architecture, reporting, and the analytics team. Set analytics strategy, oversee data engineering roadmap, build dashboards, apply statistical and ML methods, and translate insights into executive-level decisions.