IT Manufacturing Data Solutions Engineer

IT Manufacturing Data Solutions Engineer

** Date:
** Aug 12, 2026

*
* Location:

** Newton, NC, US, 28658

** Company:
** Corning

Requisition Number: 77032

** The company built on breakthroughs. ​ *
* ** Join us.​ *
* Corning is one of the world's leading innovators in glass, ceramic, and materials science. From the depths of the ocean to the farthest reaches of space, our technologies push the boundaries of what's possible.  ​ 

How do we do this? With our people. They break through limitations and expectations - not once in a career, but every day. They help move our company, and the world, forward. ​ 

​At Corning, there are endless possibilities for making an impact. You can help connect the unconnected, drive the future of automobiles, transform at-home entertainment, and ensure the delivery of lifesaving medicines. And so much more.​  

Come break through with us. 

Corning's businesses are ever-evolving to best serve our customers, industries, and consumers. Today, we accelerate and transform life sciences, mobile consumer electronics, optical communications, display, automotive, and solar markets. We are changing the world with:

+ Trusted products that accelerate drug discovery, development, and delivery to save lives

+ Damage-resistant cover glass to enhance the devices that keep us connected

+ Optical fiber, wireless technologies, and connectivity solutions to carry information and ideas at the speed of light

+ Precision glass for advanced displays to deliver richer experiences

+ Auto glass and ceramics to drive cleaner, safer, and smarter transportation

+ Solar polysilicon, wafers, and innovative photovoltaic modules, enabling low-cost solar energy solutions

** Position Summary*
* The Manufacturing Data Solutions Engineer is responsible for transforming manufacturing and operational data into actionable business intelligence, analytics, and AI-enabled solutions. This role serves as the bridge between manufacturing operations and digital technologies by developing scalable data pipelines, analytics platforms, dashboards, and reporting solutions that drive operational excellence.

The engineer works closely with Operations, Engineering, Quality, SAP, CAMSTAR and IT teams to understand manufacturing processes, integrate data from multiple systems, and deliver insights that improve productivity, quality, cost, and decision-making. The role plays a key part in Trivium's digital transformation strategy by enabling advanced analytics, machine learning, and AI capabilities across manufacturing facilities.

** Key Responsibilities*
* ** Manufacturing Data Engineering*
* + 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 platforms, databases, and other business applications.

+ Ensure manufacturing data is available, reliable, accurate, and accessible.

** Analytics & Business Intelligence*
* + 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.

** Manufacturing Systems & Process Understanding*
* + Develop expertise in manufacturing processes, production workflows, and business operations.

+ Understand data movement across MES, Historian, SAP, Oracle, SQL, and other manufacturing systems.

+ Identify opportunities to improve data quality, visibility, and process efficiency.

+ Translate manufacturing requirements into technical solutions.

** Digital Transformation & AI Enablement*
* + Support AI and advanced analytics initiatives.

+ Prepare and structure manufacturing data for machine learning and predictive analytics.

+ Partner with data scientists, engineers, and business stakeholders to develop innovative solutions.

+ Assist in evaluating emerging technologies that improve…