Manufacturing AI/ML Data Engineer Intern

NCBiotech; Charlotte (NC); On-site; USD 43,000 - 83,000; Full time

Benefits offered by this job

Competitive salaries

Housing/travel assistance

Final project presentation

Job summary

Corning in Charlotte, NC, offers a 10-week Data Engineering internship to support manufacturing, quality, and analytics initiatives. You will gain hands-on experience with enterprise datasets, cloud data platforms, and building data pipelines that enable industrial analytics.

The role emphasizes collaboration with data engineers and business stakeholders, development of dashboards, and presenting project results at the end of the term.

Qualifications

• Undergraduate or graduate student in Computer Science, Data Science, Engineering, Mathematics, Statistics, or related field.
• Strong programming skills in Python and SQL.
• Available for 10 weeks during Summer 2027 (May–August 2027) with graduation date in December 2027 or later.
• Interested in Corning, Inc after graduation if offered full-time.
• Willing to work at the posted job location.

Responsibilities

• Develop and maintain data pipelines using Python, SQL, and PySpark.
• Extract, transform, validate, and prepare data for analytics and reporting.
• Support Databricks and cloud-based data engineering projects.
• Build dashboards and data visualizations to communicate insights.
• Collaborate with data engineers, analysts, and business stakeholders.
• Document solutions and present project results at internship end.

Skills

Python

SQL

Education

CS/DS degree

Engineering degree

Math/Stats degree

Tools

Databricks

PySpark

Power BI

Tableau

AWS

Job description

Corning in Charlotte, NC, offers a 10-week Data Engineering internship to support manufacturing, quality, and analytics initiatives. You will gain hands-on experience with enterprise datasets, cloud data platforms, and building data pipelines that enable industrial analytics.

The role emphasizes collaboration with data engineers and business stakeholders, development of dashboards, and presenting project results at the end of the term.