Digital Solutions Engineer

Job Summary

/ Purpose of Role The Industrial Engineer – Digital Solutions supports process and industrial engineering operations for fiber optics connector assembly manufacturing at Corning’s RAM facility in Reynosa. This role combines industrial engineering fundamentals with programming and digital tools to reduce manual data work, connect manufacturing systems, and build scalable solutions that improve how the IE team operates.

The ideal candidate brings a continuous improvement mindset and the technical curiosity to challenge current workflows — not just learn them.

Key Responsibilities

Support industrial engineering activities across manual and semi-automatic fiber optics connector assembly lines, including time studies, capacity analysis, BOM structures and manufacturing cost modeling. Develop and maintain data solutions using Python, SQL, and Power BI to replace high-effort manual reporting and enable data-driven decision-making for the IE team.

Build integrations and automation tools that connect enterprise systems — including SAP, Windchill (Product Lifecycle Management platform), and Excel-based cost models — to reduce redundant data entry and improve data accuracy. Design and deploy lightweight web applications or internal tools that simplify repetitive or high-complexity workflows currently requiring significant manual effort from IE technicians.

Partner with IE technicians and process engineers to document current-state workflows, identify automation opportunities, and implement practical digital solutions. Apply AI tools and cloud-based data platforms (e.g., Databricks) to analyze manufacturing data and surface actionable insights for process improvement initiatives.

Maintain data integrity across manufacturing cost models and support accurate cost reporting for engineering and operations stakeholders. Support manufacturing projects related to capacity, BOM accuracy, labor and costing changes Collaborates with Operations in Manufacturing Variance Analysis Required Qualifications Bachelor’s degree in Industrial Engineering, Manufacturing Engineering, Systems Engineering, or a related field.

1+ years of experience in industrial engineering, process improvement, or manufacturing environments. Proficiency in Python for scripting, data analysis, and process automation. Proficiency in SQL for data querying, extraction, and manipulation. Proficiency in Power BI for dashboard development and manufacturing KPI (Key Performance Indicator) reporting.

Familiarity with SAP and/or Windchill (Product Lifecycle Management platform), or comparable ERP (Enterprise Resource Planning) / PLM systems, in a manufacturing context.