Senior Data Engineer

As a hybrid Data Engineer, you will be responsible for building robust data pipelines, managing data versioning, automating Machine Learning (ML) model lifecycles, and scaling infrastructure in production environments. You will act as a force multiplier, translating data science experiments into reliable, highly available, production-grade applications while maintaining robust ETL pipelines.

• Design and implement end-to-end MLOps pipelines (CI/CD/CT) to deploy, test, and maintain ML and GenAI models on AWS
• Containerize applications and build container orchestration environments
• Build, optimize, and maintain robust ETL pipelines for raw data ingestion, transformation, and storage
• Develop and manage AWS CloudFormation templates for infrastructure provisioning and environment deployment.
• Administer AWS platforms across non-production and production environments, ensuring security, availability, scalability, and reliability.
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