Data Engineering Intern: ETL, Python & SQL

re-zoo-me; Northern (KY); Hybrid; USD 30,000 - 34,000; Full time

Job summary

First Solar is seeking a Data Analytics Intern to support development of Python-based data integration and analytics solutions, including dashboard building within a Streamlit application and exposure to REST API development and SharePoint data.

You will design and build ETL pipelines retrieving information from SQL databases and SharePoint sources, transform and validate data, apply business logic checks, and make results available to analytics apps and communication channels; final

Qualifications

• Currently pursuing a bachelor’s degree in a technical field.
• Foundational experience writing Python code for data processing or development.
• Strong SQL skills including queries, joins, filters.
• Experience building ETL pipelines or moving data between systems is preferred.
• Familiarity with Git and collaborative software development.
• Exposure to Streamlit, REST APIs, SharePoint data, and CI/CD is preferred.

Responsibilities

• The Data Analytics Intern will support Python-based data integration and analytics solutions, including dashboard building in Streamlit.
• The internship includes exposure to REST API development and SharePoint data interactions.
• The major project is to design, develop, test, and document ETL pipelines retrieving info from SQL databases and SharePoint sources.

Skills

Python

SQL

Git

Streamlit

REST APIs

Data analysis

Problem solving

Communication

Education

Bachelor's degree in Computer Science or related field

Tools

Streamlit

JMP

SharePoint data

Azure DevOps

CI/CD pipelines

REST API tooling

Job description

First Solar is seeking a Data Analytics Intern to support development of Python-based data integration and analytics solutions, including dashboard building within a Streamlit application and exposure to REST API development and SharePoint data.

You will design and build ETL pipelines retrieving information from SQL databases and SharePoint sources, transform and validate data, apply business logic checks, and make results available to analytics apps and communication channels; final