Computer Data Engineer Intern/Co-op

Position Summary

The Computer Data Engineer Intern will support the design, development, and maintenance of data systems and pipelines that enable efficient data collection, storage, processing, and reporting. This internship provides hands-on experience working with large datasets, databases, cloud technologies, and data engineering best practices while collaborating with technical and business teams.

What youll do: 

• Assist in developing and maintaining data pipelines and ETL (Extract, Transform, Load) processes. 
• Support the collection, cleaning, validation, and transformation of data from multiple sources. 
• Help design and optimize database structures and data storage solutions. 
• Monitor data quality and troubleshoot data-related issues. 
• Create and maintain documentation for data workflows, systems, and processes. 
• Assist in developing reports, dashboards, and data visualization solutions. 
• Collaborate with software developers, analysts, and business stakeholders to support data initiatives. 
• Participate in testing and validating data engineering solutions. 
• Research emerging technologies and recommend process improvements. 

Position Requirements: 

• Currently pursuing a Bachelors or Masters degree in Computer Science, Data Engineering, Information Systems, Software Engineering, Mathematics, Statistics, or a related field. 
• Basic knowledge of database concepts and SQL. 
• Familiarity with programming languages such as Python, Java, or C++. 
• Understanding of data structures, algorithms, and software development principles. 
• Strong analytical and problem-solving skills. 
• Excellent written and verbal communication skills. 
• Must be authorized to work in the U.S.

Preferred Characteristics:

• Experience with relational databases such as MySQL, PostgreSQL, or SQL Server. 
• Exposure to cloud platforms such as Amazon Web Services, Microsoft Azure, or Google Cloud. 
• Familiarity with data tools such as Apache Spark, Apache Hadoop, or Apache Airflow. 
• Knowledge of data visualization tools such as Tableau or Microsoft Power BI. 
• Experience working on academic, personal, or team-based data projects.