Top Remote Analysis Reporting Jobs in Milwaukee, WI

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.

Partner with GTM, Clinical Strategy, and Finance to build and maintain dbt models, client-facing reports, and dashboards. Perform SQL-based analyses, ROI and clinical outcomes reporting, and translate insights for non-technical stakeholders. Ensure data reliability through testing, code review, and collaboration with Data Engineering; support ad-hoc requests and automation of reporting.

Lead customer-facing analytics: build dashboards, reports, and POCs that demonstrate ROI and utilization trends for healthcare provider data. Collaborate with data science and engineering on advanced models, assess and integrate new data sources, ensure data quality, and support presales and executive-facing storytelling.

Lead the vision and execution of a scalable, multi-tenant data platform: own ingestion, warehouse, transformation, BI, and AI-on-data layers. Manage and grow a data engineering team, define engineering standards (CI/CD, infra-as-code, testing, lineage), productize integrations, and collaborate with Product, Engineering, and GTM for client onboarding and data delivery.

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.

The Facets Systems Analyst will perform development and maintenance tasks in Facets, lead a team of developers, and ensure quality outcomes through testing methodologies while maintaining compliance with healthcare standards.

As a Data Engineer at Common Room, you'll build ETL pipelines, process billions of events daily, and collaborate on backend projects using AWS, Postgres, and Node.js.

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

The Data Scientist will enhance statistical models for forecasting, analyze datasets for operational planning, and communicate insights to stakeholders.

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.