Manufacturing Data Engineer: KPI & Analytics for Solar Ops

Corning Inc.; Tolleson (AZ); On-site; USD 87,000 - 119,000; Full time

Benefits offered by this job

Bonuses & incentives

401(k) matching up to 4%

Comprehensive health benefits

Job summary

Corning Inc. in Tolleson, AZ is seeking a Manufacturing Data Engineer to build the data, reporting, and analytics foundation from the ground up.

This high-impact role sits at the intersection of data engineering and manufacturing operations, owning KPI development, plant performance reporting, and analytics solutions to enable data-driven decisions. You will partner with operations, supply chain, quality, finance, and IT to define data requirements and reporting priorities, establish data

Qualifications

• Bachelor's degree in a related field or equivalent experience.
• 3+ years in data engineering, BI, analytics, or reporting.
• Experience designing data structures and reporting solutions.
• Proficiency in SQL and data transformation.
• Experience with Power BI, Tableau, or SAP reporting tools.
• Familiarity with ERP, manufacturing, or warehouse systems.
• Strong analytical and cross-functional communication.

Responsibilities

• Design, develop, and implement data structures, dashboards, scorecards, and KPI frameworks across startup and long-term operations.
• Partner with operations, supply chain, quality, finance, and IT to define data requirements and performance measures.
• Support data governance, data quality, and reporting consistency for scalable solutions.
• Identify and resolve data-related issues in reports and systems; document definitions and KPI logic.

Job description

Corning Inc. in Tolleson, AZ is seeking a Manufacturing Data Engineer to build the data, reporting, and analytics foundation from the ground up.

This high-impact role sits at the intersection of data engineering and manufacturing operations, owning KPI development, plant performance reporting, and analytics solutions to enable data-driven decisions. You will partner with operations, supply chain, quality, finance, and IT to define data requirements and reporting priorities, establish data