Co-Op Data Engineer: AI, Data & Enterprise Integration

IBM; University Park (TX); On-site; USD 49,000 - 89,000; Full time

Benefits offered by this job

Paid holidays

Paid sick time

Employee stock purchase plan

Job summary

IBM is offering a co-op internship in University Park, PA, focused on data science, AI, and enterprise integration. You will contribute to client projects across analytics, GenAI, and transformation, while developing technical and consulting skills under mentorship.

The role emphasizes learning, portfolio building, and potential progression to the Associates program based on performance. Schedule: year-long co-op with part-time during class and full-time during breaks.

Qualifications

• Pursuing a degree in Business, Information Systems, Computer Science, Engineering, or related field.
• Strong analytical and problem-solving skills.
• Excellent communication and presentation abilities.
• Familiarity with cloud, APIs, data integration, or enterprise applications is preferred.

Responsibilities

• Conduct research on integration trends, APIs, middleware, cloud platforms, and emerging technologies.
• Support assessments of business processes and application landscapes.
• Assist in developing strategy recommendations, presentations, and client deliverables.
• Analyze data and identify integration opportunities across enterprise systems.
• Participate in workshops, stakeholder interviews, and requirements gathering sessions.
• Contribute to business cases, roadmaps, and transformation strategies.
• Support project planning and change management activities.

Skills

Analytical thinking

Problem solving

Communication

Presentation

Cloud platforms

Education

Pursuing degree in Business/IS/CS/Engineering

Tools

Cloud platforms (Azure/AWS)

APIs

Job description

IBM is offering a co-op internship in University Park, PA, focused on data science, AI, and enterprise integration. You will contribute to client projects across analytics, GenAI, and transformation, while developing technical and consulting skills under mentorship.

The role emphasizes learning, portfolio building, and potential progression to the Associates program based on performance. Schedule: year-long co-op with part-time during class and full-time during breaks.