Data Engineering Intern

Job Description

Data Engineering Intern | Staffline Solutions

The Tone:
This is an internship opportunity facilitated by Staffline Solutions for their client, located remotely across the United States. The client seeks motivated individuals to build robust data infrastructure and manage large datasets using modern engineering technologies. This Data Engineering Intern position offers students and recent graduates hands-on experience in critical data infrastructure, preparing them for a career in the field. It provides a strong foundation for solving complex data challenges and working with cloud technologies while collaborating with a diverse, international team.

The TL;DR
• Role: Internship
• Type: Flexible
• Location: Remote, United States
• Team: Part of a remote data engineering team, collaborating with data analysts and data scientists.
• Mission: This person will build and maintain robust data pipelines to support efficient data processing and analysis.
• Tech Stack: Python, SQL, ETL/ELT Concepts, Data Warehousing, Apache Spark, Apache Kafka, Apache Airflow, AWS, Azure, Google Cloud, Git, Linux

What You’ll Actually Do
• Data Pipeline Development: Design, develop, and maintain robust data pipelines that facilitate efficient data flow.
• Data Handling & Validation: Collect, clean, transform, and validate data meticulously from multiple diverse sources.
• ETL/ELT Workflow Creation: Develop and support the creation of ETL/ELT workflows to ensure efficient and reliable data processing.
• Large Dataset Management: Work extensively with SQL databases and data warehouses to manage and organize large-scale datasets.
• Data System Monitoring: Monitor the quality, integrity, and overall performance across various data systems to ensure reliability.

The Must-Haves
• Background: Entry-level, requiring current pursuit or recent completion of a bachelor’s or master’s degree in computer science, data engineering, information technology, software engineering, or a related field.
• Experience: Basic knowledge of Python or Java programming; understanding of SQL and relational databases; familiarity with database concepts and data modeling; and basic knowledge of ETL processes and data pipelines.
• Skills: Strong analytical and problem-solving skills to tackle complex data challenges effectively; good communication and collaboration abilities for working with diverse teams; ability to work independently and proactively in a remote, multicultural environment; and eagerness to learn and adapt to modern data engineering tools and best practices.
• Bonus: Understanding of major cloud platforms such as AWS, Azure, or Google Cloud; basic knowledge of Apache Spark; familiarity with Apache Kafka and Apache Airflow; experience with Git & Version Control for collaborative development; and basic Linux skills.