Data Engineering Internship

Introduction

A career in IBM Consulting is rooted by long-term relationships and close collaboration with clients across the globe.

You'll work with visionaries across multiple industries to improve the hybrid cloud and AI journey for the most innovative and valuable companies in the world. Your ability to accelerate impact and make meaningful change for your clients is enabled by our strategic partner ecosystem and our robust technology platforms across the IBM portfolio; including Software and Red Hat.

Curiosity and a constant quest for knowledge serve as the foundation to success in IBM Consulting. In your role, you'll be encouraged to challenge the norm, investigate ideas outside of your role, and come up with creative solutions resulting in groundbreaking impact for a wide network of clients. Our culture of evolution and empathy centers on long-term career growth and development opportunities in an environment that embraces your unique skills and experience.

Your Role And Responsibilities

* Support the development of data pipelines: Assist in building, maintaining, and optimizing ETL/ELT workflows to ingest, process, and transform data from various sources.
* Work with cloud data platforms: Help configure, test, and monitor cloud-based data environments (e.g., Snowflake, GCP, AWS, Azure).
* Data modeling & warehousing: Contribute to the design and implementation of scalable data models, tables, and schemas used for analytics and reporting.
* Documentation: Maintain clear documentation of data processes, pipeline logic, and system configurations.
* Collaboration: Work closely with senior data engineers, analysts, and business teams to understand requirements and translate them into technical tasks.
* Learning & development: Continuously learn new tools, technologies, and best practices related to data engineering and cloud platforms.
* Automation & optimization: Assist in identifying opportunities to automate repetitive tasks and improve the performance of existing data workflows.

Required Technical And Professional Expertise

* Basic understanding of data engineering concepts and cloud data platforms.
* Interest in learning and working with modern data tools such as Snowflake or similar cloud-based technologies.
* Familiarity with fundamental data concepts such as ETL/ELT, data modeling, and data quality.
* Motivation to develop skills in cloud ecosystems and modern data frameworks.

Preferred Technical And Professional Experience

* Practical knowledge of SQL and experience writing queries for data extraction and manipulation.
* Understanding of data warehousing concepts, star/snowflake schemas, and data pipeline orchestration.
* Experience or familiarity with cloud platforms such as GCP, AWS, Azure Fabric, or Snowflake.
* Exposure to modern data engineering tools and services (e.g., BigQuery, Databricks, Dataflow...).