Intern Data Engineer 2027 – AI & Data Analytics

IBM; Chicago (IL); On-site; USD 34,000 - 48,000; Full time

Job summary

IBM internship program offers hands-on data engineering experience working on client projects across analytics, cloud data platforms, AI adoption, and GenAI. You’ll contribute to data pipelines, APIs, and governed AI-ready data, while developing technical expertise and consulting skills under mentorship.

Ideal candidates are pursuing quantitative or technical degrees, with programming familiarity (Python/SQL/Java/Scala) and a growth mindset.

Qualifications

• Currently pursuing a quantitative or technical degree in Computer Science, Data Science, MIS, Business Analytics, Systems Engineering, Industrial Engineering, Mathematics, Engineering, AI/ML, or a related field.
• Strong interpersonal skills that enhance collaboration and relationship building, while also managing dynamic workloads in an agile environment.
• Have initiative and passion to actively seek new knowledge and improve skills while embracing a growth mindset to assimilate diverse viewpoints.
• Demonstrate leadership experience and ability to communicate effectively through active listening; while also be willing to adapt and have a readiness to take ownership of tasks and challenges.
• Familiarity with programming or query languages such as Python, SQL, Java, Scala, JavaScript, or similar, and interest in data engineering concepts such as pipelines, databases, APIs, ETL/ELT, data modeling, or data quality.
• Willingness to travel as needed.

Responsibilities

• Build data engineering skills by contributing to client projects that use modern data platforms, cloud services, analytics, ML, GenAI, and agentic AI solution patterns.
• Contribute to data pipelines, data products, APIs, retrieval assets, and governed AI-ready data with guidance from IBM teams.
• Develop and maintain data ingestion, transformation, and verification processes to support analytics and client deliverables.
• Share findings and communicate data-driven insights to technical and non-technical stakeholders.

Skills

Python

SQL

Java

Scala

JavaScript

Data engineering concepts

Analytical thinking

Agile teamwork

Communication

Education

Bachelor's Degree in a quantitative/technical field

Tools

Spark

Kafka

Airflow

dbt

Databricks

Snowflake

Delta Lake

Linux

APIs

Job description

Introduction

Launch yourcareer like an IBMer

Every IBMer has a story. For many, it started with an internship.

As an IBM intern, you won't just gain experience - you'll start thinking, working, and growing like an IBMer. From day one, you'll contribute to real client projects across diverse industries, including analytics, cloud data platforms, AI adoption, generative AI, and agentic AI-enabled data transformation, working alongside experienced IBMers who are invested in your success. You'll be challenged, supported, and inspired, often all in the same day. You'll develop technical expertise and consulting skills in a culture built on continuous learning, mentorship, and coaching. High-performing interns have a clear pathway into IBM's Associate Program, launching careers at one of the world's most innovative technology and consulting companies.

To give yourself the best opportunity for success, we advise applying only to roles that align with your skills and experience, rather than applying broadly across all entry-level positions. You'll receive a status update email for each application, so be sure to check your IBM Careers account regularly — it's the best way to get a centralized view of which roles you have active applications against.

Your Role And Responsibilities

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.

Preferred Education

Bachelor's Degree

Required Technical And Professional Expertise

• Currently pursuing a quantitative or technical degree in Computer Science, Data Science, MIS, Business Analytics, Systems Engineering, Industrial Engineering, Mathematics, Engineering, AI/ML, or a related field.
• Strong interpersonal skills that enhance collaboration and relationship building, while also managing dynamic workloads in an agile environment.
• Have initiative and passion to actively seek new knowledge and improve skills while embracing a growth mindset to assimilate diverse viewpoints.
• Demonstrate leadership experience and ability to communicate effectively through active listening; while also be willing to adapt and have a readiness to take ownership of tasks and challenges.
• Familiarity with programming or query languages such as Python, SQL, Java, Scala, JavaScript, or similar, and interest in data engineering concepts such as pipelines, databases, APIs, ETL/ELT, data modeling, or data quality.
• Willingness to travel as needed.

Preferred Technical And Professional Experience

• Exposure to ETL/ELT projects, data warehouse or lake house design, data engineering capstones, data quality checks, lineage, cataloging, or data governance is a plus.
• Exposure to data engineering technologies such as Spark, Kafka, Airflow, dbt, Databricks, Snowflake, Delta Lake, Linux, APIs, or similar tools is a plus.
• Exposure to LLMs, embeddings, vector databases, retrieval systems, RAG, prompt design, MCP-based tooling, and AI-assisted Coding tools such as GitHub Copilot, Codex, Claude Code, Cursor, or similar tools for coding, testing, debugging, documentation, and code review is a plus.