The Data Engineer Intern will help build reliable, scalable data solutions that support analytics, reporting, and business operations. During this 10-week program, the intern will work with experienced data engineers on a defined project involving data ingestion, transformation, quality, and documentation.
The intern will gain practical experience with enterprise data pipelines, engineering standards, data quality practices, cloud technologies, and cross-functional delivery.
This is an entry-level, 10-week, full-time internship expected to begin in June and end in August. At this time, we are unable to provide housing or relocation assistance for this position.
Key Responsibilities
- Develop and test data pipelines under the guidance of senior engineers.
- Integrate structured and semi-structured data from multiple sources.
- Write SQL and code to transform, validate, and prepare data for analysis.
- Assist with monitoring data quality and troubleshooting pipeline issues.
- Contribute to data models, technical documentation, and source-to-target mappings.
- Participate in Agile ceremonies, code reviews, and team design discussions.
- Present project outcomes and recommendations at the end of the internship.
Basic Qualifications
- By start date, a minimum of 30 completed college-level credit hours in computer science, data engineering, information systems, software engineering, or related fields.
- Due to federal contract requirements, United States Citizenship or Permanent Work Authorization is required.
Preferred Qualifications
- A completed bachelor’s degree and enrollment verification in a master’s program or 9 credit hours complete in graduate coursework in computer science, data engineering, information systems, software engineering, or a related field.
- Academic or project experience with SQL and at least one programming language, preferably Python, Java, or Scala.
- Familiarity with databases, data structures, ETL/ELT concepts, or cloud platforms.
- Strong analytical, problem-solving, and communication skills.
- Ability to work both independently and collaboratively.
- Interest in enterprise data architecture, cloud data platforms, and responsible data
- management.
- Exposure to Azure, AWS, Google Cloud, Databricks, Snowflake, Spark, or similar technologies.
- Familiarity with Git, APIs, data warehouses, or orchestration tools.
- Experience gained through coursework, research, personal projects, or prior internships.