Gallup The Data Engineering Intern at Gallup assists in building and modernizing data tools, infrastructure, and pipelines. The role involves working with Python and SQL to support data engineering practices and collaborating with technical leaders.
Responsibilities
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
Qualification
Enrollment in an associateComfort using AI tools such as ClaudeUnderstanding of ETL/ELT concepts
Required
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
Anticipated graduation between August 2027 and May 2028 preferred
Availability to work 40 hours per week for 12 weeks during the summer of 2027 required
Preferred
Understanding of ETL/ELT concepts
Familiarity with cloud data platforms and warehouses (AWS, Snowflake, Redshift)
Exposure to pipeline orchestration or transformation tooling such as Apache Airflow, dbt or Apache Spark
Familiarity with version control and collaborative development using Git or GitHub
Anticipated graduation between August 2027 and May 2028
