Top Analysis Reporting Jobs in Milwaukee, WI

Own lightweight data governance and operational reporting: define/document business terms, maintain a data catalog, build SQL-based operational datasets and reports, monitor data quality, diagnose anomalies, and align stakeholders across BizTech, Analytics, and business teams.

Build and maintain cloud data pipelines and ML feature/model workflows in Snowflake and AWS. Implement data ingestion, transformations, quality checks, monitoring, and documentation. Collaborate with data scientists, analysts, and product teams to support analytics, audience insights, rapid prototyping, and reliable production deployments.

The Senior Analytics Engineer will design and build scalable data pipelines using dbt and Snowflake, providing technical guidance, conducting audits, and mentoring junior engineers while leveraging AI tools to enhance productivity.

Design, develop, and optimize Tableau dashboards and data sources on Redshift; collaborate with data engineering (dbt) and business teams; own Tableau governance, performance tuning, documentation, training, and ensure data security compliance.

The Junior Manual QA Engineer will execute test cases, perform exploratory testing, document bugs, and collaborate with teams to ensure high-quality software. This role involves learning QA methodologies and improving testing processes alongside experienced professionals.

The Senior Analyst, People Analytics analyzes workforce data, translates business questions into KPIs, and collaborates with various teams to deliver insights and reporting solutions.

As a Business Operations Associate, you'll drive data-driven decisions and strategies, analyze performance metrics, and optimize operations for growth at Jerry.ai.

The role involves executing advanced analytics, applying statistical techniques, designing reporting capabilities, and translating business needs into analytical solutions while ensuring data integrity and communicating insights effectively.

The role involves designing scalable data architectures, developing data pipelines, engaging with stakeholders, ensuring security and governance, and leveraging AI tools for data processing in the Databricks environment.

Develop and maintain data pipelines and reporting tools, support real-time processing workflows, and collaborate with teams to enhance platform capabilities, utilizing Java, Python, and Groovy scripts.