Data Engineer Intern: Cloud Pipelines & ML Prep

plymouthrock; Boston (MA); On-site; USD 34,000 - 41,000; Full time

Job summary

Plymouth Rock is seeking a Data Engineer Intern/Co-op in Boston to help modernize data pipelines and enable analytics initiatives within Enterprise Advanced Analytics.

You will partner with data scientists to build Python + SQL ingestion pipelines from SQL Server and cloud sources into AWS, ensure data quality, and document workflows.

This role offers hands-on exposure to SageMaker data prep, cloud-native tooling, and a fast-growing analytics culture in the heart of Boston.

Qualifications

• Pursuing or holding a Master’s in CS, IS, or Data Engineering.
• Experience building Python + SQL data pipelines.
• AWS services (S3, Glue, Step Functions) familiarity.
• Experience with SQL Server and performant SQL.
• Comfort with Linux and bash; able to debug jobs.
• Experience with CI/CD, Git, and basic testing.
• Exposure to on-prem data extraction or VPN connections.
• Familiarity with Parquet, partitioning, and data lake practices.
• Exposure to CloudWatch and Datadog monitoring.
• Interest in ML data prep for SageMaker.

Responsibilities

• Assist in modernizing legacy data pipelines into Python-based, cloud-native workflows using AWS.
• Build ingestion pipelines moving data from SQL Server and other sources into AWS S3 data lake.
• Improve pipeline performance, scalability, and cost efficiency.
• Implement data quality checks and idempotent runs.
• Contribute to reusable Python modules for ingestion and transformations.
• Collaborate with data scientists to prepare datasets for SageMaker training.
• Document code, workflows, and runbooks; keep docs current.

Skills

Python

SQL

Data pipelines

Linux

Git

CI/CD

Testing

Education

Master’s in Computer Science

Tools

S3

AWS Glue

AWS Step Functions

SQL Server

Linux Bash

Job description

Plymouth Rock is seeking a Data Engineer Intern/Co-op in Boston to help modernize data pipelines and enable analytics initiatives within Enterprise Advanced Analytics.

You will partner with data scientists to build Python + SQL ingestion pipelines from SQL Server and cloud sources into AWS, ensure data quality, and document workflows.

This role offers hands-on exposure to SageMaker data prep, cloud-native tooling, and a fast-growing analytics culture in the heart of Boston.