Top Remote Data & Analytics Jobs in Richmond, VA

Lead legacy-to-SaaS data migrations: design and execute ETL, extract/transform/load data, validate integrity, map business workflows to target models, engage clients, document processes, support governance, and train stakeholders to ensure accurate, secure conversions.

The Database Administrator will manage Oracle Banner ERPs, supporting installations, upgrades, and configurations while ensuring database security and performance.

The HR Data Analyst will lead data transformation to SuccessFactors, develop reports, ensure data quality, and train users on data tools.

The Business Systems Analyst will analyze business requirements, document processes, and develop scalable solutions for Salesforce to enhance sales operations.

Analyze complex people data to identify trends and risks, leveraging automation for improved efficiency. Collaborate on people strategies and initiatives, providing actionable insights through data analysis.

Lead risk modeling initiatives from data exploration to deployment, defining methodologies, advising clients, and integrating models into platforms.

The Principal, Advanced Analytics - Subscriber Forecasting leads forecasting methodologies and develops frameworks for subscriber volume forecasting, integrating advanced analytics, time-series modeling, and AI. Responsibilities include scenario planning and cross-functional collaboration to inform enterprise decision-making.

The Data Governance Liaison ensures data governance accuracy and compliance, automates data catalog processes, conducts audits, and promotes awareness within the organization.

The Lead GTM Analytics Engineer designs and manages the data model for GTM execution, ensuring accurate metrics and insights across Sales, Marketing, Customer Success, and Partnerships to drive revenue performance.

Build and operate scalable data pipelines and analytics-ready datasets using Python, dbt, and BigQuery. Develop Looker dashboards, ensure data quality and observability, optimize performance and cost, integrate data workflows with backend services and CI/CD, and support analytics, experimentation, and production use cases.