Top Analysis Reporting Jobs in Madison, WI

Design, build, and maintain end-to-end batch and streaming data pipelines; develop ETL/ELT workflows and modular Python code; write and optimize SQL; implement analytics data models; monitor data quality, troubleshoot failures, and document pipelines; collaborate with stakeholders and mentor teammates. Remote role for candidates based in Latin America.

Lead design and execution of data migration strategies for Salesforce Revenue Cloud (CPQ & Billing). Define data architecture, mappings, and transformation logic; build SQL-based extraction and ETL processes; perform iterative test loads, reconciliation, and validation. Collaborate with clients and cross-functional teams to manage cutovers, documentation, and migration quality for quote-to-cash data.

The Data Scientist will work with the team to build and optimize models, interpret data, and support product development using massive data sets for advertising effectiveness.

As a Data Engineer, you will build and optimize data pipelines, manage ETL workflows, and ensure efficient data access and quality within the infrastructure.

Lead design, build, and optimization of Sezzle's large-scale data warehousing and pipelines. Own data infrastructure KPIs/SLAs, improve Redshift performance, evolve the data stack, implement ETL/ELT workflows, and partner with cross-functional teams to deliver reliable, scalable datasets.

Lead the architecture and design of an operational data platform, focusing on data unification, streaming integrations, governance, and mentoring teams while ensuring HIPAA compliance.

The Data Analyst will maintain KPI standards for Customer Support, build dashboards, produce analyses, and lead metric alignment conversations, ensuring accurate data interpretation and decision-making support.

Design and maintain data systems for business-critical insights, connect data across platforms, build ETLs, and support business data decisions.

Support JDA/Blue Yonder WMS, configure systems for customer implementations, test new code, and collaborate with teams for operational improvements.

The Principal Data Platform Engineer leads the architecture and development of the enterprise data platform, focusing on analytics, data science, and AI/ML capabilities. They establish standards for data quality and observability, design data ingestion and processing patterns, and mentor team members to enhance technical capabilities.