Data Engineering Internship

Expand your knowledge and apply for our internship!

What should you know before applying?

The internship is an essential part of an engineer's career. It is an excellent opportunity to enter the IT world, a very dynamic place where learning continues. During the internship which lasts three weeks, interns are working alone on tasks that simulate real-life ones. With a help of a mentor, they are able to acquire the experience they usually don’t have a chance to gain at college.

Companies that offer such internship programs have standards and expectations from students who engage in the practice. And, Vega IT is one of them.

Our primary goal is to create high-quality data engineering solutions through innovative approaches. As a Data Engineering Intern, you will focus on designing and optimizing ETL pipelines, using tools like Apache Airflow to orchestrate workflows, and ensuring that data flows seamlessly across systems. You will be responsible for building data models using SQL that align with business requirements and developing efficient, scalable pipelines to support analytics and data-driven decision-making across the organization. This hands-on experience will deepen your understanding of data architecture and inspire creative problem-solving with real-world applications.

Here is the list of things that Vega IT expects from every person who applies for the internship:

• Proficiency in SQL: Experience in writing efficient queries and working with relational databases.
• Familiarity with ETL Tools: Knowledge of ETL processes for data extraction, transformation, and loading. Familiarity with AirFlow is a plus
• Programming Skills: Strong foundation in Python, especially in data processing libraries like Pandas and Polars and experience with data pipelines.
• Data Modeling: Understanding of data modeling concepts, including schema design and normalization.
• Cloud Platforms: Familiarity with cloud-based data storage and processing platforms (e.g., AWS, Azure, or Google Cloud) is a plus.
• Analytical Mindset: Ability to analyze and solve complex data problems with attention to detail.
• Eagerness to Learn: A passion for learning new tools and technologies in data engineering.
• Collaboration and Communication: Strong team player with effective communication skills.
• Proactive Attitude: Self-motivated and eager to contribute to improving data pipelines and processes.
• Familiarity with Git for collaboration and version management.
• Proficiency in spoken and written English

Open-mindedness and people skills are something that we value. Therefore candidates with these characteristics have better chances to work with us.