Remote AI Data Engineer - Python & AWS Pipelines

Cognizant; Santa Fe (NM); Remote; USD 100,000 - 115,000; Full time

Benefits offered by this job

Medical/Dental/Vision/Life Insurance

401(k) plan and contributions

Paid holidays plus Paid Time Off

Long-term/Short-term Disability

Paid Parental Leave

Employee Stock Purchase Plan

Job summary

Cognizant Technology Solutions Corporation is seeking an AI Data Engineer to design and optimize scalable cloud-native data engineering solutions for AI-driven applications. You will collaborate with data engineers, software engineers, architects, and stakeholders across the AWS ecosystem.

Responsibilities include building data pipelines, integrating with enterprise platforms, and deploying Lambda functions while ensuring code quality and rigorous testing.

Qualifications

• Strong hands-on Python development experience with production-quality code.
• Proven data engineering experience building scalable data pipelines.
• Hands-on expertise with AWS services and cloud-native architectures.
• Experience with AWS Glue, AWS DMS, Kafka, Airflow, or Snowflake.
• Experience using AI-assisted development tools to accelerate software engineering.

Responsibilities

• Design, build, and optimize scalable cloud-native data pipelines and processing solutions.
• Develop production-grade Python applications and AWS Lambda functions.
• Improve data platforms using AWS Glue, DMS, Kafka, Airflow, and Snowflake.
• Translate requirements into technical designs and acceptance criteria.
• Review and optimize AI-generated code to ensure engineering rigor.

Skills

Python development

Data engineering

AWS services

Tools

AWS Glue

AWS DMS

Apache Kafka

Apache Airflow

Snowflake

Claude Code

Kiro

TypeScript

Job description

Cognizant Technology Solutions Corporation is seeking an AI Data Engineer to design and optimize scalable cloud-native data engineering solutions for AI-driven applications. You will collaborate with data engineers, software engineers, architects, and stakeholders across the AWS ecosystem.

Responsibilities include building data pipelines, integrating with enterprise platforms, and deploying Lambda functions while ensuring code quality and rigorous testing.