Data Modeling Analytics & AI Engineering

Required Qualifications

3+ years of hands-on experience with AWS services, including EKS, EC2, S3, IAM, CloudWatch, and ECR.

Strong experience operating and troubleshooting Kubernetes (preferably AWS EKS).

Proficiency in containerization (Docker) and orchestration concepts.

Strong programming/scripting experience in Python and Bash.

Experience building and managing CI/CD pipelines (GitLab or equivalent).

Familiarity with machine learning workflows, including training, inference, and model monitoring.

Experience with infrastructure-as-code (Terraform or CloudFormation).

Experience supporting production platforms, including incident management and root cause analysis.

Preferred Qualifications

Experience managing Data Analytics Platforms / Tools (e.g., Domino, SageMaker)

Experience with ML lifecycle tools such as MLflow, or similar.

Experience supporting GPU-based workloads or distributed training environments.

Familiarity with enterprise MLOps architectures and patterns (batch, real-time, microservices).

Understanding of data processing frameworks and feature pipelines