Data Engineering Intern — Build Scalable Pipelines

Greystar Worldwide, LLC; Northern (KY); Hybrid; USD 43,000 - 62,000; Part time

Benefits offered by this job

Employee Assistance Program

Paid sick time

Job summary

Greystar offers a Data Engineering Internship where you will design data pipelines using Python, PySpark and SQL, collaborating with data scientists and architects to deliver scalable solutions. You will gain hands-on experience ingesting data into big data platforms and support decision-making with insights.

The role emphasizes building repeatable processes, improving data quality, and producing enterprise-level code, with opportunities to learn across multiple enterprise systems.

Qualifications

• Quantitative background and analytical problem-solving ability.
• Strong working knowledge of Python, PySpark, SQL, GitHub and Excel/PowerPoint.
• Clear written and verbal communication skills with attention to detail.
• Enrolled in a graduate degree program in Data Engineering or Data Analytics, graduating Dec 2027–May 2028.

Responsibilities

• Design and develop data pipelines using Python, PySpark and SQL.
• Use coding agents to speed up delivery of data pipelines.
• Operationalize data pipelines and improve data quality across systems.
• Collaborate with data scientists and data architects on projects.
• Generate documentation ready for business use.

Skills

Python

PySpark

SQL

GitHub

Excel

PowerPoint

Communication

Education

Graduate degree program in Data Engineering or Data Analytics

Tools

Azure DevOps

Slack

Microsoft Teams

Cursor

Claude

GitHub Copilot

Job description

Greystar offers a Data Engineering Internship where you will design data pipelines using Python, PySpark and SQL, collaborating with data scientists and architects to deliver scalable solutions. You will gain hands-on experience ingesting data into big data platforms and support decision-making with insights.

The role emphasizes building repeatable processes, improving data quality, and producing enterprise-level code, with opportunities to learn across multiple enterprise systems.