Engineering Manager, Data Platforms & AI (Hybrid)

Cigna Healthcare; Georgia; Hybrid; USD 147,000 - 167,000; Full time

Benefits offered by this job

Health benefits

401(k) plan

Tuition reimbursement

Paid time off (at least 18 days)

Life insurance

Job summary

The Cigna Group is seeking a Software Engineering Manager to lead a data-focused software engineering team in a hybrid environment. You will guide architecture, build scalable data solutions, and collaborate with data scientists and governance to deliver impactful applications.

Key responsibilities include designing systems with AWS, Elasticsearch, Python, and GraphQL, and integrating AI-generated data to improve user outcomes.

Qualifications

• Healthcare domain experience required.
• Experience creating Python ETL scripts for data pipelines.
• Experience with REST API integrations for data movement.
• Proficiency with relational databases (PostgreSQL) and graph databases.
• DevOps and CI/CD practices in Agile environments.
• Designing and implementing Python standalone apps and ETL processes.
• Building scalable data processing systems and data migrations.

Responsibilities

• Collaborate with data scientists and governance teams to define and deliver data solutions.
• Provide technical leadership in architecture and technology decisions.
• Design and implement applications using AWS, Elasticsearch, React, Python, and GraphQL.
• Incorporate AI-generated data to enhance end-user value.
• Translate requirements into technical specifications and design criteria.
• Ensure compliance with architectural standards and enterprise guidelines.
• Support hybrid work schedule.

Skills

AWS

Elasticsearch

React

Python scripting

GraphQL

Education

Bachelor’s degree in Computer Science

Master’s degree

Tools

PostgreSQL

Graph databases

CI/CD

DevOps practices

Hadoop ecosystem

REST API integrations

Job description

The Cigna Group is seeking a Software Engineering Manager to lead a data-focused software engineering team in a hybrid environment. You will guide architecture, build scalable data solutions, and collaborate with data scientists and governance to deliver impactful applications.

Key responsibilities include designing systems with AWS, Elasticsearch, Python, and GraphQL, and integrating AI-generated data to improve user outcomes.