Top Analysis Reporting Jobs in Baltimore, MD

Senior, hands-on role defining enterprise data architecture and standards across cloud platforms (Snowflake, Databricks, Azure). Design data models, integration patterns, governance, and pipelines to support analytics and AI/ML. Lead platform decisions, ensure security, metadata, and MDM; mentor teams and drive architecture reviews and documentation.

The Senior Privacy Manager will lead complex privacy consulting engagements, mentor a team of privacy professionals, and guide client initiatives across various regulations while fostering a collaborative team culture.

Own end-to-end data pipelines for multiple clients: extract, clean, transform, model and visualize data. Build dashboards and automated workflows, apply AI where useful, and present actionable insights to non-technical stakeholders.

The Senior Analytics Engineer will design and build scalable data pipelines using dbt and Snowflake, providing technical guidance, conducting audits, and mentoring junior engineers while leveraging AI tools to enhance productivity.

The Data Analyst will build key data models and metrics for decision-making, partner with stakeholders for analytical insights, create datasets for self-service reporting, and ensure data reliability through quality checks.

The Lead Data Platform Engineer will design and build Virtuous's data platform, ensuring it is secure, scalable, and AI-ready. Responsibilities include architecting access controls, optimizing performance, and enabling self-service analytics while maintaining governance and compliance standards.

As a Salesforce Technical Architect focused on Data & AI, you'll design and implement solutions using Salesforce Data 360, oversee technical projects, collaborate with various stakeholders, and mentor junior staff to drive AI innovations.

Develop and maintain Epic Healthy Planet registries and analytics solutions: gather requirements, profile Epic source data, build rules/metrics/dashboards, provide ad-hoc analysis, support end users, document solutions, and mentor users.

Manage data transformation programs, develop strategies, and maintain client relationships for technology advisory in AI and analytics. Lead diverse teams and ensure program execution meets quality standards.

The Data Engineer will develop and maintain data pipelines, build data models, ensure data quality, and support cross-functional teams while improving internal data platform infrastructure and documentation.