Data Engineering Intern

January 26

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Description

β€’ About the Internship: This 3-month hands-on training internship is an opportunity to learn real-world, practical skills in data engineering while working on real projects that impact the industry. β€’ What You’ll Learn: β€’ Data Pipeline Development: Build and manage scalable ETL (Extract, Transform, Load) pipelines for data processing. β€’ Data Warehousing: Learn to design and optimize data storage for high-performance analytics. β€’ Big Data Tools: Gain hands-on experience with industry-standard tools like Apache Spark, Hadoop, and more. β€’ Cloud Platforms: Work with cloud services like AWS, Google Cloud, or Azure for data storage and analytics. β€’ Data Integration: Learn how to integrate data from multiple sources and maintain data quality. β€’ SQL & Python Programming: Build expertise in writing efficient queries and leveraging Python for data manipulation. β€’ Real-World Problem Solving: Participate in solving real-world challenges by contributing to live projects. β€’ Version Control & Collaboration: Use Git and agile methodologies to work collaboratively with a team.

Requirements

β€’ Passion for Data Engineering: A strong interest in data systems, analytics, and solving complex problems. β€’ Technical Skills: Basic knowledge of SQL, Python, or any other programming language. Familiarity with data structures is a plus. β€’ Curiosity & Willingness to Learn: Open to new tools, technologies, and methodologies. β€’ Team Player: Excellent communication and collaboration skills. β€’ Education: Computer Science, Data Science, or a related field (students or recent graduates preferred).

Benefits

β€’ Practical, real-world experience working on live data engineering projects. β€’ Mentorship from experienced professionals with deep industry expertise. β€’ A portfolio of completed projects to showcase your skills. β€’ Networking opportunities and a letter of recommendation upon successful completion of the program. β€’ A stepping stone toward a career in data engineering, data science, or related fields.

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