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DATA ENGINEER INTERN @ CUBEGLE TECHNOLOGIES PVT LTD

India, Ahmedabad Posted 3/23/2026 cubegle.com 2448 Views
Cubegle Technologies Pvt LTD is seeking a motivated and detail-oriented individual to join our team as a Data Engineer Intern. This role is designed for candidates who are passionate about data and eager to kickstart their career in the field of data engineering. During this full-time internship, you will have the unique opportunity to gain hands-on industry experience by working on real-world data projects. You will work alongside experienced professionals in a friendly and growth-oriented environment that encourages learning and professional development. The primary focus will be on supporting data infrastructure and participating in various stages of the data lifecycle.

As an intern, you will apply your knowledge of SQL, Python, and Power BI to assist in building and maintaining data pipelines. You will gain exposure to essential data concepts such as ETL (Extract, Transform, Load), Cloud ETL, and data warehousing principles. The internship is based at our Ahmedabad office located at Link, 100 FT, RCC ROAD, near JLR Showroom, Upper, Gota. We are looking for candidates who possess strong analytical skills and a proactive approach to problem-solving. This position is an excellent stepping stone for anyone looking to build a solid foundation in the data engineering industry while contributing to meaningful projects.

Key Requirements

Basic knowledge of SQL and database management systems. Familiarity with Power BI for data visualization and reporting. Proficiency in Python programming for data manipulation. Foundational understanding of data concepts including ETL and Cloud ETL. Basic understanding of data warehousing architecture and principles. Eagerness to learn and grow within the fast-paced data field. Strong analytical and logical reasoning capabilities. Excellent written and verbal communication skills. Ability to work effectively in a collaborative team environment. Strong attention to detail and commitment to data accuracy.

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