The Cigna Group

Technology Development Program – Data & Analytics Engineering Track

The Cigna Group

full-time

Posted on:

Origin:  • 🇺🇸 United States

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Salary

💰 $70,300 - $117,100 per year

Job Level

Mid-LevelSenior

Tech Stack

AWSCloudJavaScriptPythonReactSQLTableau

About the role

  • Work within the Data & Analytics Engineering track, contributing to the design, development, and optimization of data pipelines, platforms, and analytical tools.
  • 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.
  • Participate in structured learning through both core and track-specific curriculum including technical training and leadership development.
  • Build meaningful relationships across the organization through networking events, mentorship, cross-functional collaboration, or informal peer engagement.

Requirements

  • Education: Full time candidates must have completed a bachelor’s or master’s degree in a technical program at the time of hire.
  • Preferred degrees include Computer Science, Data Science, Machine Learning, and Artificial Intelligence.
  • Other degrees are considered with coding experience such as Statistics, Mathematics, Robotics, Healthcare Analytics, or Bioinformatics.
  • Familiarity with programming languages and tools such as Python, JavaScript, SQL, R, React, Power BI, AWS and relevant skills like Prompt Engineering or Tableau.
  • AI-Native Mindset: Naturally integrates AI tools and techniques into data workflows—leveraging machine learning, generative AI, and automation to accelerate analysis, enhance predictions, and improve data-driven decision-making.
  • Academic coursework, projects, research, or internships that demonstrate hands-on experience with data modeling, analytics, machine learning, or business intelligence.
  • Leadership or involvement in student organizations, analytics clubs, or technical competitions (e.g., data hackathons, Kaggle challenges, case competitions).