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IBM

IBM Internship Data Engineer with Snowflake

IBM

Published 16 May 2026
Bucharest, Romania
Internship

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Role Highlights

Languages used

SQL

Key skills

Data Engineer
Data Architect
Integrations
CICD
Cloud
AI
Infrastructure
Deployment
ETL
ELT
Architecture

Tools, Libraries and Frameworks

IOS
Red Hat
IBM
SnowFlake

Description

The intern will assist in the development of a Snowflake-based Data Hub by supporting the setup and integration of non-production environments. Responsibilities include ensuring alignment with organizational infrastructure standards and contributing to deployment pipelines and code repositories. The role involves establishing automated CI/CD processes to streamline development workflows. Additionally, the intern will support the integration of central job control to enable orchestrated ETL/ELT workflows. Collaboration with infrastructure teams is required to ensure all implementations remain secure and compliant.

Required Qualifications and Skills

Candidates are required to possess basic knowledge of SQL and Python, along with an understanding of data engineering concepts and ETL/ELT processes. Applicants should demonstrate an interest in Snowflake or cloud-based data platforms and a willingness to learn CI/CD, deployment pipelines, and orchestration tools. The role requires the ability to collaborate effectively with technical infrastructure teams. No specific degree or professional qualifications are explicitly stated as requirements for this position.

Disclaimer

Disclaimer: Job and company description information and some of the data fields may have been generated via GPT-4 summarisation and could contain inaccuracies. The full external job listing link should always be relied on for authoritative information.

About the company

IBM

Size

305978

Website

ibm.com

HQ

Armonk, New York, US

Public/Private

Public Company

Description

IBM infuses core business operations with intelligence, from machine learning to generative AI, to make organizations more responsive, productive, and resilient. It helps clients put AI into action now, creating real value with trust, speed, and confidence across various areas like digital labor, IT automation, and security. The ability to utilize all data is critical, as AI's effectiveness is dependent on the quality of data fueling it, with IBM's AI, and data platform aiming to scale and accelerate AI's impact with trusted data. IBM's hybrid cloud platform offers a comprehensive approach to development, security, and operations across hybrid environments, laying a flexible foundation for leveraging data wherever it resides.

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