Top Data Analyst Jobs

Support SAP Master Data Governance (MDG) initiatives focused on Material Master: gather and document requirements, assist backlog creation, design business processes, support and troubleshoot MDG applications and interfaces, collaborate with technical teams, develop and execute functional/regression/integration tests, and contribute to continuous process improvements.

Build, maintain, and operate ETL/ELT data pipelines for an enterprise data platform. Support deployment via IaC, monitor and troubleshoot pipelines, run data quality checks, document processes, and collaborate with senior engineers to test and deploy features in a mission-critical government environment.

Analyze CI/CD, project management, and log data to identify bottlenecks and automation opportunities; build dashboards (Tableau/Power BI); quantify automation impact; present findings and document analytical processes.

Perform healthcare data research, analysis, and reporting focused on Epic Tapestry and managed care measures (HEDIS, P4P, HCC/RAF, PMPM). Develop BI reports/dashboards, present insights to stakeholders, handle ad hoc requests, and obtain required Epic and data-model certifications.

Research, evaluate, and manage partnerships with data providers. Assess datasets for coverage and interoperability, support deal structuring, maintain partnership pipeline, and collaborate with product, engineering, and legal to integrate data into the platform.

As a Senior Data Analyst, you will analyze data, create reports, manage data pipelines, and provide insights to influence product decisions. You will collaborate with various teams and perform A/B testing.

The role involves data architecture, data analysis, governance, and quality management within SAP systems, requiring advanced technical and leadership skills.

Lead core business analytics: build and maintain KPI dashboards, run statistical analyses and A/B tests, identify drivers of retention and revenue, support forecasting, partner with Product/Engineering to improve data quality, and use AI/scripting to automate analytics and surface insights for leadership.

Analyze and report on inclusion, diversity, equity, and engagement data. Provide insights to support IDE&E programs, and prepare presentations for executive leadership.