Top Analysis Reporting Jobs in Providence, RI

Lead the evolution of data platform by designing scalable pipelines, improving data processes, mentoring teams, and modernizing data architecture.

The Senior Business Analyst will lead end-to-end process discovery and define workflows utilizing AI and automation to improve operational efficiency.

The Data Engineer will help build modern data infrastructure, designing ETL pipelines, modeling datasets, and collaborating with teams for improved data quality and accessibility.

The Manager, Data Success Management oversees Data Success Managers, manages data operations, supports partners, improves workflows, and ensures data quality.

Lead Pager Health’s enterprise data and reporting strategy, build a centralized data and reporting shared services function, own internal dashboards and client-facing analytics, partner with Product and Engineering on data architecture and governance, mentor data teams, prioritize and deliver data initiatives, and drive continuous improvement in tooling, automation, and data storytelling to support growth, efficiency, and client outcomes.

The Data Migration Engineer migrates customer data into SaaS products, ensuring data quality and business continuity while collaborating with teams and managing customer requirements.

Lead a team of data and infrastructure engineers to develop cloud-based data systems and solutions for analytics, ensuring best practices in data management and MLOps.

The Data Platform Engineer II role involves automating data infrastructure, scaling analytics platforms, and ensuring system reliability and security. Key responsibilities include managing CI/CD pipelines, configuring secure networking, and collaborating with Data & Analytics teams to optimize performance.

The Senior Reporting & Analytics Consultant leads customer-focused reporting and analytics engagements, developing solutions, supporting implementations, and training clients, while ensuring project success.

As a Senior Data Engineer, you will design and maintain scalable data models, build production data pipelines, and support analytics across various business functions.