Manufacturing Data Engineer: AI, Analytics & BI

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

Benefits offered by this job

Company-wide bonuses

100% company-paid pension

Health and well-being benefits

Paid time off

Employee Assistance Program

Recognition program

Job summary

Corning Incorporated is seeking a Manufacturing Data Solutions Engineer to transform manufacturing data into actionable insights. You will build scalable data pipelines, analytics platforms, and AI-enabled solutions.

You’ll collaborate with Operations, Engineering, Quality, SAP, CAMSTAR and IT to drive digital transformation across facilities. You will design ETL/ELT processes, develop data models, and deliver dashboards and reports to improve productivity, quality, and cost.

Qualifications

• Bachelor’s degree in computer science, information systems, data engineering, computer engineering, analytics, or equivalent experience.
• Minimum 3+ years of experience in data engineering, business intelligence, analytics, or manufacturing systems.
• Experience supporting MES manufacturing or industrial environments.
• Experience developing reporting and analytics solutions for business users.
• Experience integrating data across multiple enterprise platforms.
• Databricks, SQL, Python, Apache Spark.
• ETL / ELT Development and Data Pipeline Design.
• Data Modeling and Data Warehousing Concepts.
• Oracle and SQL Server.
• Manufacturing Data Integration.
• Power BI, DAX, Dashboard Development, Requirements Gathering.
• Business Process Analysis.
• System Integration.

Responsibilities

• Design, develop, and maintain data pipelines within Databricks.
• Build and support ETL/ELT solutions for manufacturing data integration.
• Develop scalable data models and datasets for reporting, analytics, and AI solutions.
• Integrate data from manufacturing systems, historians, ERP, databases, and other apps.
• Ensure manufacturing data is available, reliable, and accessible.
• Design and develop Power BI dashboards, reports, and KPI scorecards.
• Create standardized manufacturing metrics and reporting solutions.
• Support operational performance monitoring through analytics and visualization.
• Perform root cause analysis and trend analysis using manufacturing data.
• Deliver actionable insights that improve quality, throughput, downtime, and cost performance.
• Develop expertise in manufacturing processes, production workflows, and operations.
• Understand data movement across MES, Historian, SAP, Oracle, SQL, and other systems.
• Identify opportunities to improve data quality, visibility, and efficiency.
• Translate manufacturing requirements into technical solutions.
• Support AI and advanced analytics initiatives.
• Prepare and structure manufacturing data for machine learning and predictive analytics.
• Partner with data scientists, engineers, and stakeholders to develop solutions.
• Assist in evaluating emerging technologies that improve manufacturing performance.
• Support image analytics, predictive maintenance, quality analytics, and Industry 4.0 initiatives.
• Work with Operations, Engineering, Quality, and Leadership.
• Gather requirements and translate to technical specs.
• Present analytics findings to stakeholders.
• Promote data-driven decision making.

Skills

Databricks

SQL

Python

Apache Spark

ETL/ELT Development

Data Modeling

Data Warehousing

Oracle

SQL Server

Power BI

DAX

Dashboard Development

Requirements Gathering

System Integration

Manufacturing Data Integration

Education

Bachelor’s degree in Computer Science / Information Systems / Data Engineering or equivalent

Tools

CAMSTAR

Job description

Corning Incorporated is seeking a Manufacturing Data Solutions Engineer to transform manufacturing data into actionable insights. You will build scalable data pipelines, analytics platforms, and AI-enabled solutions.

You’ll collaborate with Operations, Engineering, Quality, SAP, CAMSTAR and IT to drive digital transformation across facilities. You will design ETL/ELT processes, develop data models, and deliver dashboards and reports to improve productivity, quality, and cost.