Senior DevOps & Data Engineer (AWS Cloud)

LeadPatron; Buenos Aires; Híbrido; ARS 185.448.000 - 247.265.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Competitive compensation

Comprehensive benefits

Flexible work environment

Descripción de la vacante

Proofpoint is seeking a Senior DevOps and Data Engineer to join our Data Platform team in a hybrid capacity. You will own reliability, automation, and delivery of systems powering data pipelines and analytics across AWS-based infrastructure.

You will build CI/CD pipelines, manage Terraform/AWS CDK stacks, and lead observability for data workflows. Collaboration with data engineers, scientists, and security teams is essential to deliver scalable data products.

Formación

• 5+ years of professional experience in DevOps, platform engineering, or site reliability engineering, with at least 2 years of hands-on data engineering work.
• Deep expertise with AWS core services: S3, IAM, VPC, CloudWatch, Lambda, ECS/EKS, Secrets Manager, and CloudFormation/CDK.
• Hands-on experience with AWS data services: Glue, Athena, and S3 lifecycle/encryption.

Responsabilidades

• Design, implement, and maintain CI/CD pipelines for automated testing, deployment, and promotion of AWS Glue ETL jobs, Athena views, and data infrastructure.
• Build and manage cloud infrastructure on AWS using IaC (Terraform and/or AWS CDK).
• Own the observability stack for data pipelines with metrics, logs, and alerts.

Conocimientos

5+ years DevOps

AWS core services

CI/CD

Observability

Strong communication

Herramientas

Terraform

AWS CDK

GitHub Actions

Jenkins

Docker

Kubernetes

MWAA/Airflow

Lambda

Glue

Descripción del empleo

Proofpoint is seeking a Senior DevOps and Data Engineer to join our Data Platform team in a hybrid capacity. You will own reliability, automation, and delivery of systems powering data pipelines and analytics across AWS-based infrastructure.

You will build CI/CD pipelines, manage Terraform/AWS CDK stacks, and lead observability for data workflows. Collaboration with data engineers, scientists, and security teams is essential to deliver scalable data products.