Top Senior Analysis Reporting Jobs in Dayton, OH

The Senior Data Engineer will scale and evolve the data platform, develop ETL/ELT pipelines, establish best practices, and optimize systems for performance while collaborating with various teams.

The Senior Data Analyst will collaborate across teams to provide insights, build analytics databases, create dashboards, and automate reporting solutions. They will analyze data trends and partner with IT and product teams to enhance data models.

As a Sr. Staff Deployment Strategist, you will drive business transformation by partnering with clients to design and implement AI-powered data intelligence solutions, ensuring value realization and client integration.

The Risk Portfolio Analytics Manager leads risk reporting and analytics, ensuring a data-driven view of risk exposure and portfolio performance. Responsibilities include producing reports for governance bodies, monitoring performance, enhancing fraud analytics, and improving reporting frameworks.

The Senior Specialist supports growth through data-driven insights and performance analysis, translating data into actionable insights, and collaborating with cross-functional teams.

The Sr. GTM Analytics Analyst leads analytics initiatives, manages cross-functional projects, develops data assets, and conducts in-depth analyses to inform business decisions.

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.

The Sr. BI Engineer will design and maintain dashboards, support Sisense queries, optimize data reporting, and collaborate with various departments to enhance data visualizations and analytics.

The Partner Solutions Engineer drives partner engagement, supports enterprise opportunities, creates enablement materials, and translates customer challenges into solutions, all geared towards scaling partner-sourced revenue.

As a Senior Data Engineer, you'll transform raw data into datasets, design production pipelines, integrate customer data, and collaborate with various teams to ensure data quality and reliability.