Cigna Group's Technology Development Program - Data & Analytics Engineering Track Summer Internship

The Cigna Group’s Technology Development Program (TECDP) Data Analytics Engineering Internship

Get ready to embark on an exhilarating summer adventure with The Cigna Group’s Technology Development Program Summer Internship! We are on the lookout for passionate individuals who are eager to dive into the world of technology and make a real difference in healthcare. Over the course of 12 dynamic weeks, you’ll have the chance to work on impactful technology projects, receive comprehensive training, and benefit from invaluable mentorship that will supercharge your career.

Work within the Data & Analytics Engineering track, contributing to the design, development, and optimization of data pipelines, platforms, and analytical tools. You’ll gain hands‑on experience transforming raw data into actionable insights, deepening your skills in data architecture, engineering, and visualization while helping drive data‑informed decision‑making across The Cigna Group.

Engage with peers, mentors, and cross‑functional partners through community‑building activities and collaborative initiatives. Whether you’re supporting recruiting efforts, driving innovation, promoting community, or enhancing onboarding experiences, you’ll learn by doing and growing through shared knowledge.

Participate in structured learning through both core and track‑specific curriculum. This includes technical training, leadership development, and exposure to the business designed to support your growth as a well‑rounded technologist.

Build meaningful relationships across the organization through networking events, mentorship, cross‑functional collaboration, or informal peer engagement. Develop strong relationships that support your personal and professional growth.

Currently pursuing a degree in Data Science, Computer Science, Information Technology, or a related field, with an emphasis on data engineering and analytics.

Strong understanding of data modeling, ETL (Extract, Transform, Load) processes, and data warehousing concepts.

Proficiency in programming languages such as Python, Java, or Scala for data manipulation and analysis.

Experience with SQL for database querying and data management, along with familiarity with No

SQL databases such as MongoDB or Cassandra.

Basic knowledge of data visualization tools such as Tableau, Power BI, or similar platforms to present data insights effectively.

Familiarity with big data technologies such as Hadoop, Spark, or cloud‑based data services such as AWS, Google Cloud, or Azure is a plus.

Strong analytical and problem‑solving skills, with the ability to work with large data sets and derive meaningful insights.

Good understanding of data governance and data quality concepts, with attention to data accuracy and integrity.

Excellent verbal and written communication skills to collaborate with cross‑functional teams and convey technical information clearly.

A proactive attitude toward learning and enthusiasm for staying current on trends and technologies in data analytics engineering.

A GPA of 3.3 or higher is preferred.

The role requires a hybrid work schedule, with a minimum of three days per week working onsite (Tuesday, Wednesday, and one additional day of the employee’s choice), and the option to work the remaining days remotely. Employees must be able to meet the onsite schedule.

You must be available to work a 40‑hour work week beginning May 24th, 2027. Working days are Monday – Friday.

The anticipated hourly pay range for this role is $25.00 to $33.00 per hour. Actual compensation will be determined based on factors…