Innovation & Technology Internship – Data Engineering – Summer 2027 (Undergraduate)

CVS Health•Irving, TX

3d•Hybrid

About The Position

This is a 10.5-week, full-time undergraduate internship running from May 24, 2027, through August 4, 2027. The role is hybrid and based in Irving, Texas, with three in-office days per week, generally Tuesday through Thursday, and two days that may be worked remotely. Relocation assistance is provided for candidates who need to relocate more than 50 miles. The Data Engineering intern works alongside experienced data engineers, data scientists, and business partners to build the data foundations that support analytics, machine learning, and AI across CVS Health. The intern develops data pipelines, integrates data from multiple sources, and helps ensure large-scale health care data is reliable and ready for use. The work contributes to solutions aimed at improving health care quality, affordability, and outcomes. The internship includes business projects, community service activities, professional development workshops, mentorship and networking opportunities, and interaction with senior leaders. Innovation & Technology interns also participate in a Leadership Insight Series, an Intern Innovation Challenge, and learning experiences on topics such as presentations and storytelling, emerging technology, and AI tools. The hourly pay range is $35.00–$38.50. The internship includes two days of paid leave and no work on the July 4 company holiday. Work visa sponsorship, including CPT, OPT, and F-1 Visa programs, is not available. The posting also describes the position as part-time in its benefits section, while the internship summary identifies it as full-time.

Requirements

Currently pursuing a bachelor's degree with an expected graduation date between December 2027 and June 2028.
Experience using Python to process, transform, and automate data workflows.
Experience using SQL to query and analyze data.
Exposure to cloud platforms such as GCP, AWS, or Azure.

Nice To Haves

Preferred fields of study include Computer Science, Computer Engineering, Data Engineering, Information Systems, or a related technical field.
Knowledge of data warehousing and ETL concepts, including data pipelines and transformation.
Experience building data engineering solutions in cloud environments, preferably GCP.
Familiarity with Git, CI/CD pipelines, and Bash/UNIX scripting.
Experience integrating data from APIs and disparate sources using multiple tools and languages.
Strong problem-solving and critical-thinking skills applied to complex data and engineering problems.
Ability to clearly explain technical concepts and their implications to technical and non-technical audiences.

Responsibilities

Build, test, and maintain data pipelines that extract, transform, and load data.
Integrate structured and unstructured data from multiple sources and systems.
Implement data quality checks to ensure data is accurate, complete, and consistent.
Develop and deploy data solutions in cloud environments.
Contribute to solutions that improve health care quality, affordability, and outcomes.