Intern Data Engineer 2027 - AI & Data Analytics

During your internship, you can build data engineering skills by contributing to client projects that use modern data platforms, cloud services, analytics, machine learning, GenAI, and agentic AI solution patterns. This role provides an opportunity to build a compelling portfolio, acquire new skills, gain insight into diverse industries, and contribute to client-ready data pipelines, data products, APIs, retrieval assets, and governed AI-ready data with guidance from IBM teams.

At IBM, we prioritize continuous learning, skill development, and personal growth within a culture of coaching and mentorship. As an intern, you'll strengthen technical, analytical, and consulting skills while learning data quality, observability, governance, and responsible AI practices, and you could advance to our full-time Associates program based on results and performance.

Work experiences you could be exposed to:

• Mentored Data Engineering Support: Receive mentorship from data engineers, architects, AI engineers, consultants, and technical mentors while applying analytical rigor, data modeling, data quality, and responsible AI practices to client challenges.
• Data Pipeline and Platform Development: Develop skills in writing efficient, reusable code to ingest, transform, validate, model, and serve structured, semi-structured, and unstructured data for analytics, RAG, and agentic AI solution components.
• Effective Communication: Assisting explaining data flows, data quality, lineage, pipeline health, assumptions, limitations, and recommendations to both technical and non-technical audiences.
• Tech-Driven Data Builder: Use tools such as Python, SQL, cloud platforms, ETL/ELT tools, APIs, data platforms, and AI-assisted coding tools to turn raw data sources into reliable analytical and AI-ready assets.