Digital Solutions Engineer

Corning Incorporated; Reynosa; Sur place; MXN 420 000 - 600 000; Plein temps

Résumé du poste

Corning Incorporated in Reynosa is seeking an Industrial Engineer – Digital Solutions to blend IE fundamentals with programming to reduce manual data work and connect manufacturing systems. You will build scalable digital tools and data-driven solutions for the IE team.

The ideal candidate has a continuous improvement mindset and the technical curiosity to challenge current workflows, partnering with technicians and process engineers to implement practical digital solutions.

Qualifications

• Bachelor’s degree in Industrial Engineering, Manufacturing Engineering, Systems Engineering, or 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 KPI reporting.
• Familiarity with SAP and/or Windchill or comparable ERP/PLM systems in manufacturing.

Responsabilités

• Support IE activities across manual and semi-automatic assembly lines, including time studies and cost modeling.
• Develop and maintain data solutions using Python, SQL, and Power BI to automate reporting.
• Build integrations connecting SAP, Windchill, and Excel-based cost models to reduce data entry and improve accuracy.
• Design lightweight internal apps to simplify workflows currently requiring manual effort.
• Collaborate with technicians and process engineers to document and automate current-state workflows.

Connaissances

Python

SQL

Power BI

SAP/Windchill

Formation

Bachelor’s degree in Industrial Engineering or related field

Description du poste

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.