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

CVS Health•New York, NY

3d•Hybrid

About The Position

The Innovation & Technology – Data Engineering Internship is a 10.5-week, full-time internship running from May 24, 2027, through August 4, 2027. It is a hybrid position based in New York, NY, with three in-office days per week, generally Tuesday through Thursday, and two days that may be worked remotely. Relocation assistance is available for candidates who need to relocate more than 50 miles. The intern will work alongside data engineers, data scientists, and business partners to build data foundations that support analytics, machine learning, and AI across CVS Health. The work includes developing data pipelines, integrating data from multiple sources, and helping ensure large-scale health care data is reliable and ready for use. The internship includes business projects, community service, professional development workshops, mentorship and networking, interaction with senior leaders, a Leadership Insight Series, an Intern Innovation Challenge, and learning experiences on presentations, storytelling, emerging technology, and AI tools. The hourly pay rate is $51.60, based on a 40-hour workweek. The internship includes two days of paid leave and no work on the July 4 company holiday. Corporate interns may have an increased likelihood of receiving an offer for a future CVS Health role. Work visa sponsorship is not available, including for CPT, OPT, and F-1 Visa programs.

Requirements

Currently pursuing a master'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.