Data Platform Engineer Intern — Hybrid, Build Pipelines

CarGurus Early Careers; Boston (MA); Hybrid; USD 62,000 - 66,000; Full time

Benefits offered by this job

Hybrid work model

Daily free lunch

New car discount

Meditation and fitness apps

Commuting cost coverage

Job summary

CarGurus is seeking a Data Platform Engineer Intern to join the Data Engineering team for an 11-week Summer Internship. This full-time role (40 hours per week) runs June through August 2027 and offers hands-on experience building data pipelines and expanding our warehousing platform.

The position is hybrid, based in our Boston, MA office about 60% on-site. You will work with Python, SQL, Airflow, and Terraform, gaining exposure to ETL/ELT, data modeling, and testing in a collaborative

Qualifications

• Pursuing a Bachelor's or Master's degree with eligibility for a full-time internship.
• Interest in data engineering and building scalable data pipelines and infrastructure.
• Proficiency in Python and SQL and willingness to learn.

Responsibilities

• Understand and contribute to the evolving data and analytics stack.
• Support decisions around the Data Engineering domain and data pipelines.
• Help build robust data integration pipelines (ETL/ELT) using Python, SQL, and Airflow.
• Write clean, testable data pipeline code and handle errors.
• Collaborate with stakeholders to develop testing.
• Deploy and manage data infrastructure with Terraform.

Skills

Python

SQL

Airflow

ETL/ELT

Fivetran

Terraform

Data modeling

Education

Bachelor's or Master's in CS/IS/Data

Tools

Airflow

Terraform

SQL tooling

Job description

CarGurus is seeking a Data Platform Engineer Intern to join the Data Engineering team for an 11-week Summer Internship. This full-time role (40 hours per week) runs June through August 2027 and offers hands-on experience building data pipelines and expanding our warehousing platform.

The position is hybrid, based in our Boston, MA office about 60% on-site. You will work with Python, SQL, Airflow, and Terraform, gaining exposure to ETL/ELT, data modeling, and testing in a collaborative