Senior AWS Data Platform & DevOps Engineer

Maxit Consulting - Max Corporate Group; Buenos Aires; Hybrid; ARS 139,086,000 - 200,903,000; Full time

Benefits offered by this job

Competitive compensation

Comprehensive benefits

Flexible work environment

Job summary

Proofpoint is seeking a Senior DevOps and Data Engineer to own reliability and automation across data pipelines and analytics infrastructure. You will manage cloud infrastructure on AWS (Iac), CI/CD for Glue ETL jobs, and data workflows, enabling fast, safe delivery of data products.

The role emphasizes hands-on data engineering, observability, and collaboration with data scientists, security teams, and engineers. A hybrid workplace supports collaboration across teams.

Qualifications

• 5+ years of professional experience in DevOps, platform engineering, or site reliability engineering.
• Hands-on data engineering work (2+ years) and AWS core services like S3, IAM, VPC, CloudWatch, Lambda, ECS/EKS.
• Proficiency with IaC tools (Terraform / CDK) and CI/CD across multiple ecosystems.

Responsibilities

• Design, build, and maintain CI/CD pipelines for AWS Glue ETL jobs and data infrastructure.
• Own cloud infrastructure on AWS using IaC, including S3, IAM roles, Glue, Athena workgroups, and networking.
• Develop observability through metrics, logs, and alerts to ensure SLA compliance and rapid incident response.
• Build self-service DataOps tooling, templates, and reusable libraries for production pipelines.

Skills

DevOps & SRE experience

AWS core services

Data engineering

CI/CD pipelines

Infrastructure as code

Container orchestration

Observability & monitoring

Tools

Terraform

AWS CDK

Docker

Kubernetes

Apache Airflow

Job description

Proofpoint is seeking a Senior DevOps and Data Engineer to own reliability and automation across data pipelines and analytics infrastructure. You will manage cloud infrastructure on AWS (Iac), CI/CD for Glue ETL jobs, and data workflows, enabling fast, safe delivery of data products.

The role emphasizes hands-on data engineering, observability, and collaboration with data scientists, security teams, and engineers. A hybrid workplace supports collaboration across teams.