Data & Analytics Engineering Intern - Tech Development Program (Summer)

Cigna Health and Life Insurance Company; Bloomfield (CT); Hybrid; USD 34,000 - 45,000; Full time

Benefits offered by this job

Hybrid schedule

Job summary

The Cigna Group is seeking talented individuals for its TECDP Data Analytics Engineering Internship. Over 12 weeks, interns will work on data pipelines, analytics, and visualization, gaining hands-on experience and mentorship to accelerate a career in health tech.

Qualified candidates are pursuing data science or CS degrees, with skills in Python/SQL, data modeling, ETL, and BI tools, and a willingness to learn modern big data technologies. Hybrid schedule with onsite and remote days.

Qualifications

• Currently pursuing a degree in Data Science, Computer Science, Information Technology, or related field.
• Strong understanding of data modeling, ETL processes, and data warehousing concepts.
• Proficiency in Python, Java, or Scala for data manipulation and analysis.
• Experience with SQL for querying and NoSQL databases like MongoDB or Cassandra.
• Familiarity with data visualization tools such as Tableau or Power BI.

Responsibilities

• Work within the Data & Analytics Engineering track to design, develop, and optimize data pipelines and analytics tools.
• Transform raw data into actionable insights and support data-driven decision making.
• Engage with peers and cross-functional partners through mentorship and collaboration.
• Participate in structured curriculum including technical training and leadership development.

Skills

Python

SQL

NoSQL

Data modeling

ETL

Tableau

Power BI

Hadoop

Spark

AWS

Big data

Education

Data Science

Computer Science

Tools

MongoDB

Cassandra

Job description

The Cigna Group is seeking talented individuals for its TECDP Data Analytics Engineering Internship. Over 12 weeks, interns will work on data pipelines, analytics, and visualization, gaining hands-on experience and mentorship to accelerate a career in health tech.

Qualified candidates are pursuing data science or CS degrees, with skills in Python/SQL, data modeling, ETL, and BI tools, and a willingness to learn modern big data technologies. Hybrid schedule with onsite and remote days.