Data Engineering Intern: Snowflake, Python & Cloud Data

Fashion Institute of Design & Merchandising; Omaha, Northern (NE, KY); Hybrid; USD 17,000 - 23,000; Full time

Job summary

HDR is seeking a motivated Data Engineering Intern for Summer 2027 to help design, build, and maintain scalable data systems using Snowflake and Python. You will collaborate with data scientists, analysts, and software engineers to support enterprise-level data solutions.

You’ll gain practical experience with modern cloud data technologies and contribute to data pipelines across the organization, including ETL/ELT processes, data quality, and performance tuning.

Qualifications

• Pursuing a Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or related field.
• Strong Python programming skills and knowledge of SQL.

Responsibilities

• Assist in designing, developing, and maintaining scalable data pipelines using Python and SQL.
• Work with Snowflake to ingest, transform, and manage large datasets.
• Support ETL/ELT pipeline design for collecting, transforming, and loading data from multiple sources.
• Collaborate with data engineers and analysts to ensure data quality and integrity.
• Participate in code reviews, documentation, and agile development practices.
• Support automation of data workflows and performance tuning efforts.
• Explore and implement best practices in data engineering and cloud data architecture.

Skills

Python

SQL

Cloud computing

Data pipelines

Analytical thinking

Communication

Education

Bachelor's or Master's in CS/DS/Engineering

Tools

Snowflake

Git

Job description

HDR is seeking a motivated Data Engineering Intern for Summer 2027 to help design, build, and maintain scalable data systems using Snowflake and Python. You will collaborate with data scientists, analysts, and software engineers to support enterprise-level data solutions.

You’ll gain practical experience with modern cloud data technologies and contribute to data pipelines across the organization, including ETL/ELT processes, data quality, and performance tuning.