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# Business Analytics Lead

- **Company:** Kaivac, Inc.
- **Location:** Hamilton, OH, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Business Analytics Applications, Data Warehousing, Power BI, Standard Sql, Tableau (Software), Microsoft Fabric, Data Lakes, Data Analytics
- **Published:** July 9, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=0f644b1e9cf22da8

## About the Role

* Experience building dashboards using tools like Grow, Power BI, Tableau, or similar
 * 3-5+ years of experience in data analytics, business intelligence, or a related role
 * Strong working knowledge of SQL or similar tools for working with data
 * Experience working with data across multiple systems (ERP, CRM, etc.)
 * Experience administering data lake and data warehouse systems (Microsoft Fabric, Grow, etc.)
 * Ability to translate business questions into clear data insights
 * Strong communication skills and comfort working with non-technical teams
 * Self-starter who can operate in an evolving environment and help build structure, * Dashboard development: 2 years (Required)
 * Data analytics: 2 years (Required)

## Description

Kaivac is seeking a Business Analytics Lead build and scale our data and analytics capabilities. This role will help transition the organization from reactive reporting to a more structured, self-service analytics environment-enabling teams to access insights, make better decisions, and reduce reliance on IT for day-to-day data needs.

What You'll Do

 * Take ownership of reporting and dashboard development to support business decision-making
 * Build and improve dashboards that allow teams to access and explore data independently
 * Analyze and organize data from multiple systems (ERP, CRM, etc.) into a more structured, usable format
 * Partner with teams across Sales, Operations, and Finance to understand data needs and translate them into actionable insights
 * Improve data quality and consistency by helping define standards and best practices
 * Reduce reliance on ad hoc reporting by creating scalable, repeatable analytics solutions
 * Support early-stage efforts to better structure data for future AI and advanced analytics initiatives
 * Balance day-to-day reporting needs with longer-term improvements to data and analytics capabilities


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