Process Transformation Business Intelligence Data Analyst

General Motors in Warren, MI (hybrid) is seeking a Process Transformation BI Data Analyst to automate business processes, deliver self-service reports and dashboards for Global Purchasing and Supply Chain, and derive insights from large datasets using ETL, SQL, Python, KNIME, Power BI and related tools, with knowledge of agentic AI and LLMs.

Responsibilities

• Partner with business units, IT, and analytics stakeholders to identify, prioritize, and document opportunities for deeper insights, close data gaps, and drive efficiency
• Lead and support service line modernization initiatives from requirements gathering through user acceptance
• Translate large volumes of data from structured and unstructured sources into actionable insights to inform business decisions
• Educate and assist business users in adopting self-service tools and dashboards, clarifying available data fields and underlying logic
• Produce documentation and analytical reports that summarize results, assumptions, and conclusions

Requirements

• A minimum of 3 years of relevant industry experience; internships or co-ops are not considered
• Bachelor’s degree required in data analytics, engineering, computer science, operations management, supply chain, or related field
• Self-starter with the ability to influence others, working in teams and independently with customers, cohorts, and partners across multiple locations
• Demonstrated ability to build customer-facing dashboards using a tool such as Power BI
• Experience extracting large datasets with SQL
• Working knowledge of ETL best practices and experience transforming data with Python, Power Query, KNIME, or similar tools

Technologies

• KNIME
• Power Automate
• Power BI
• SQL
• Python
• Power Query
• SAP Ariba
• SAP MM
• SAP FI
• R
• SAS
• agentic AI
• LLM

What will give you a competitive edge (Preferred Qualifications)

• Knowledge of Source to Pay processes and working knowledge of SAP Ariba, SAP MM, or SAP FI
• Experience using statistical programming languages to produce advanced analytics (Python, R, or SAS)
• Familiarity with agentic AI and large language models, plus a demonstrated interest or success in automating business processes