Data Engineer Intern - Cloud Pipelines & Analytics

National Information Solutions Cooperative (NISC); Lake Saint Louis (MO); Hybrid; USD 28,000 - 41,000; Full time

Benefits offered by this job

Mentorship

Future opportunities

Enterprise projects

Job summary

National Information Solutions Cooperative (NISC) is seeking a Data Engineer Intern to join the Data Engineering team in a hybrid role based near Lake Saint Louis, MO. You will work on data pipelines, learn data architecture with AWS and Databricks, and collaborate across software, analytics, and product teams.

You will gather, clean, and transform data for analytics, contribute to documentation, and explore automation to improve workflows.

Qualifications

• Familiarity with SQL and at least one programming language (e.g., Python, Java, or Scala).
• Pursuing a bachelor’s degree or post secondary education in data science or computer science related field.

Responsibilities

• Assist in building and maintaining data pipelines that support analytics and application development.
• Learn about and contribute to data architecture using AWS and Databricks.
• Help gather, clean, and transform data from various sources into usable formats.
• Collaborate with software developers, data analysts, and product teams to understand data needs.
• Participate in team meetings, code reviews, and brainstorming sessions.
• Explore opportunities to automate manual processes and improve data workflows.
• Contribute to documentation and internal knowledge sharing.
• Leverage generative AI tools and technologies to enhance productivity, creativity, and problem-solving within the scope of the role.

Skills

SQL

Python

Java

Scala

Git

Problem solving

Team collaboration

Education

Pursuing bachelor’s degree in CS/Data Science

Tools

Airflow

Databricks

AWS

Spark

ETL

Job description

National Information Solutions Cooperative (NISC) is seeking a Data Engineer Intern to join the Data Engineering team in a hybrid role based near Lake Saint Louis, MO. You will work on data pipelines, learn data architecture with AWS and Databricks, and collaborate across software, analytics, and product teams.

You will gather, clean, and transform data for analytics, contribute to documentation, and explore automation to improve workflows.