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# IT Manufacturing Data Solutions Engineer

- **Company:** Corning
- **Location:** Newton, NC, United States
- **Experience:** Experienced
- **Salary:** $82,051.0 - $112,821.0
- **Contract:** Permanent contract
- **Skills:** Adaptable Database Systems, Artificial Intelligence, Business Analytics Applications, Data Analysis, Microsoft Azure, Business Software, Cloud Computing, Information Systems, Databases, Computer Engineering, Information Engineering, Data Integration, Extract Transform Load (ETL), Data Warehousing, Python (Programming Language), Machine Learning, Microsoft SQL Server, Operational Data Store, Oracle (Applications), Power BI, SAP (Applications), SQL Databases, Systems Integration, Technical Data Management Systems, Apache Spark, Information Technology, Data Pipelines, Databricks
- **Published:** August 11, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=4258cff9137c8987

## About the Role

Bachelor's degree in computer science, Information Systems, Data Engineering, Computer Engineering, Analytics, or equivalent experience to be considered.
Minimum of 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

Preferred Qualifications

Experience supporting digital transformation initiatives.
SAP integration experience.
Knowledge of CAMSTAR manufacturing systems.
Experience with AI, machine learning, and predictive analytics.
Cloud platform experience (Azure preferred).
Certifications in Databricks, Power BI, or Cloud.
Experience supporting multi-site manufacturing operations.

## Description

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 manufacturing performance.
Support image analytics, predictive maintenance, quality analytics, and other Industry 4.0 initiatives.

Collaboration & Stakeholder Engagement

Work closely with Operations, Engineering, Quality, and Manufacturing leadership.
Gather business requirements and translate them into technical specifications.
Present analytics findings and recommendations to business stakeholders.
Promote adoption of data-driven decision-making across the organization.
Serve as a trusted technical advisor for manufacturing analytics solutions.


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