Manufacturing Data Solutions Engineer: AI & Analytics

Corning Inc.; Newton (NC); On-site; USD 82,000 - 113,000; Full time

Benefits offered by this job

Company-wide bonuses

Long-term incentives

401(k) matching

Health benefits and wellness programs

Job summary

Corning is seeking an IT Manufacturing Data Solutions Engineer to transform manufacturing data into actionable insights. You will design data pipelines, dashboards, and AI-enabled analytics, collaborating with Operations, Engineering, and IT to drive productivity and quality across sites.

The role focuses on data engineering, data integration, and advanced analytics within a manufacturing context, with opportunities to apply AI/ML to improve outcomes and enable digital transformation.

Qualifications

• Bachelor’s degree in computer science, information systems, data engineering, or equivalent.
• Minimum 3+ years in data engineering, BI, analytics, or manufacturing systems.
• Experience supporting MES manufacturing environments.
• Experience developing reporting/analytics for business users.
• Experience integrating data across multiple enterprise platforms.
• Knowledge of Databricks, ETL/ELT, data modeling, data warehousing, Oracle and SQL Server.

Responsibilities

• Design, develop, and maintain data pipelines within Databricks.
• Build and support ETL/ELT data integration solutions.
• Develop scalable data models and datasets for reporting, analytics, and AI.
• Integrate data from MES, historians, ERP, databases, and other apps.
• Ensure data availability, reliability, and accuracy.

Skills

Databricks

ETL / ELT Development

Data Modeling

Data Warehousing

Power BI

System Integration

Education

Bachelor's degree in Computer Science or equivalent

Tools

Oracle

SQL Server

CAMSTAR

Azure

Job description

Corning is seeking an IT Manufacturing Data Solutions Engineer to transform manufacturing data into actionable insights. You will design data pipelines, dashboards, and AI-enabled analytics, collaborating with Operations, Engineering, and IT to drive productivity and quality across sites.

The role focuses on data engineering, data integration, and advanced analytics within a manufacturing context, with opportunities to apply AI/ML to improve outcomes and enable digital transformation.