Data Engineering Intern

Apply early for priority consideration. Gallup has limited openings for this internship, and the position will be filled quickly.

As a data engineering intern at Gallup, you’ll help build and modernize the data tools, infrastructure and pipelines that enable teams to work with data at scale. Alongside experienced technical leaders, you’ll put your Python and SQL skills to work on meaningful projects while learning best practices, experimenting with modern tools and seeing firsthand how strong data engineering supports better decisions.

What You’ll Do

During your internship, you will:

• Build foundational data tooling and infrastructure designed to scale as the volume and frequency of data grow
• Help modernize legacy data pipelines using Python, SQL and Gallup’s evolving data platform
• Troubleshoot data quality issues in large, imperfect datasets
• Apply data engineering practices to move, transform and validate data across systems
• Help build reliable, efficient data workflows
• Learn from senior technical leaders who will mentor you on engineering practices, tools and approaches
• Collaborate with engineers and interact directly with stakeholders to understand needs and deliver useful solutions
• Use AI-enabled development tools to improve the quality and efficiency of your work

What You Need

• Enrollment in an associate, bachelor’s or graduate degree program in computer science, data engineering, information systems, statistics, math or a related field required
• Classroom or work experience writing SQL required, including joins, aggregations and troubleshooting query performance
• Classroom or work experience coding in Python for data processing, scripting or automation required
• Working knowledge of relational database and data modeling concepts, including schema design and dimensional or star-schema modeling, required
• Comfort using AI tools such as Claude, Claude Code or GitHub Copilot to support high-quality, efficient work required
• Understanding of ETL/ELT concepts and how data are moved, transformed and validated between source systems and a warehouse preferred
• Familiarity with cloud data platforms and warehouses (e.g., AWS, Snowflake, Redshift) preferred
• Exposure to pipeline orchestration or transformation tooling such as Apache Airflow, dbt or Apache Spark preferred
• Familiarity with version control and collaborative development using Git or GitHub preferred
• Enrollment at a college or university within an 80-mile radius of San Francisco, California, required