Top Senior Analysis Reporting Jobs in Madison, WI

The Data Engineer Senior will optimize data pipelines, work within scrum teams, mentor others, and improve data quality, reliability, and governance.

The role involves supporting sales and services initiatives through data analysis, relationship management, and cross-functional collaboration to inform strategies and optimize processes.

The Senior Data Architect designs and implements data architecture solutions, leveraging modern platforms and methodologies to enhance data management, modeling, and integration across applications and stakeholders.

The IBM TM1 Developer will manage the SDLC for Finance applications, focusing on TM1 and migrating from Essbase, while collaborating with global teams.

As a Senior Data Analyst, you'll provide actionable insights by analyzing product and engineering data, partnering with leadership on metrics frameworks and decision support for product delivery.

The Senior Korean Linguist manages translation and copy-editing tasks, coordinates with freelancers, and ensures high-quality Korean-language deliverables while improving workflows and supporting quality efforts.

Design, develop, and maintain enterprise Power BI dashboards and reports. Integrate data from SQL Server, Azure, Excel and other sources, perform data modeling and DAX calculations, validate data, and document data models and reporting logic while partnering with business stakeholders.

Design, build, and scale data pipelines and integrations for the TDX platform. Implement REST API integrations, ingest and unify customer data, optimize pipelines for performance and quality, ensure data security and governance, and collaborate with Product, Data Science, and customer teams to deliver reliable analytics-ready data.

The Director of Analytics will lead the analytics strategy and operations for a top-grossing mobile app, driving data-driven decision-making and insights.

Lead analytics engineering: architect, build, and maintain scalable data pipelines and dbt models; ensure data is research-ready; partner with Engineering, Data Science, and Commercial teams; implement product analytics and optimize data workflows for scale.