Data Engineering Intern: Build AI Pipelines & Models

Rysun Labs Inc; Milpitas (CA); Hybrid; USD 25,000 - 38,000; Part time

Job summary

Rysun Labs Inc. is seeking a motivated Data Engineer Intern to join our growing data team in a hybrid role across Tampa, FL and Milpitas, CA. You will help build data pipelines, support AI/ML initiatives, and work with large-scale data platforms in a collaborative environment.

The ideal candidate is passionate about data, analytics, and emerging AI technologies. Bring hands-on pipeline experience and a desire to learn in a fast-paced setting.

Qualifications

• Interest in data, analytics, and emerging AI technologies.
• Hands-on experience with building data pipelines or ETL/ELT workflows.
• Eager to learn in a collaborative, fast-moving team environment.

Responsibilities

• Data Pipeline Development: design, build, and maintain scalable ETL/ELT pipelines for ingesting diverse data into a modern data lakehouse.
• AI-Ready Data Foundations: cleanse and structure data for AI/ML use cases, including feature engineering and embeddings prep.
• Data Modeling: assist in developing enterprise data models with dimensional modeling approaches.
• Performance Tuning: monitor and optimize pipeline execution times, queries, and storage patterns.
• Data Quality & Governance: implement automated checks and monitor data drift for analytics reliability.
• Collaboration: work in an agile setting with data engineers, scientists, and stakeholders.

Skills

ETL pipelines

SQL

Data modeling

Feature engineering

Python

Education

Pursuing Bachelor's in CS/SE/Data Science

Tools

Airflow

Spark

BigQuery

Job description

Rysun Labs Inc. is seeking a motivated Data Engineer Intern to join our growing data team in a hybrid role across Tampa, FL and Milpitas, CA. You will help build data pipelines, support AI/ML initiatives, and work with large-scale data platforms in a collaborative environment.

The ideal candidate is passionate about data, analytics, and emerging AI technologies. Bring hands-on pipeline experience and a desire to learn in a fast-paced setting.