Senior DevOps & Data Engineer - AWS Data Pipelines

Fullstack; Buenos Aires; Hybrid; ARS 184,482,000 - 276,723,000; Full time

Job summary

Proofpoint is seeking a Senior DevOps and Data Engineer to join our Data Platform team. This hybrid role sits at the intersection of platform engineering and data infrastructure, owning reliability, automation, and delivery of data pipelines and analytics capabilities.

You'll build and maintain cloud infrastructure on AWS, implement CI/CD pipelines, and contribute to data pipelines using Glue, Athena, and S3. Collaboration across engineering, security, and data teams is essential.

Qualifications

• 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 (ETL jobs, Crawlers, Data Catalog), Athena (workgroup management, query tuning, federated queries), and S3 (lifecycle, encryption, event notifications).
• Proficiency with Infrastructure-as-Code tools-Terraform and/or AWS CDK-for managing production cloud environments.
• Strong CI/CD experience: designing and maintaining pipelines in GitHub Actions, Jenkins, GitLab CI, or equivalent.
• Experience with container technologies (Docker) and container orchestration (Amazon ECS, EKS, or Kubernetes).
• Proven ability to design and operate observability systems (metrics, logging, distributed tracing, alerting) for data and platform services.
• Strong communication skills-able to translate operational concerns into clear engineering trade‑offs for both technical and non‑technical audiences.

Responsibilities

• Design, implement, and maintain CI/CD pipelines for automated testing, deployment, and promotion of AWS Glue ETL jobs, Athena views, and related data infrastructure.
• Build and manage cloud infrastructure on AWS using Infrastructure-as-Code (Terraform and/or AWS CDK) - covering S3 buckets, IAM roles, Glue resources, Athena workgroups, Lake Formation permissions, VPCs, and supporting services.
• Own the observability stack for data pipelines: define and instrument metrics, logs, and alerts (CloudWatch, Datadog, or equivalent) to ensure SLA compliance and fast incident response.
• Develop and maintain the DataOps platform - self-service tooling, pipeline templates, and shared libraries that allow data engineers to spin up production-grade pipelines quickly.
• Manage container and compute infrastructure (Docker, ECS/EKS, or Lambda) used to support data ingestion microservices and orchestration workers.
• Design and operate workflow orchestration environments (Amazon MWAA / Apache Airflow, AWS Step Functions) including upgrades, scaling, and reliability hardening.
• Build and maintain AWS Glue ETL jobs (PySpark) for large-scale data ingestion and transformation across the data lake on S3.
• Drive security best practices across the data platform: secrets management (AWS Secrets Manager / Parameter Store), least-privilege IAM, network segmentation, and compliance controls.
• Collaborate with data engineers, data scientists, and security teams to translate requirements into scalable, automated infrastructure solutions.
• Lead incident response for data platform outages: on-call participation, root-cause analysis, and post-mortem-driven improvements.
• Mentor junior engineers on DevOps and data engineering practices, conduct code and design reviews, and contribute to architecture decision records.

Skills

AWS core services

CI/CD pipelines

Terraform / AWS CDK

Docker

ECS/EKS/Kubernetes

Data engineering

Observability

Incident response

Communication

Tools

GitHub Actions

Jenkins

GitLab CI

Terraform

AWS CDK

Job description

Proofpoint is seeking a Senior DevOps and Data Engineer to join our Data Platform team. This hybrid role sits at the intersection of platform engineering and data infrastructure, owning reliability, automation, and delivery of data pipelines and analytics capabilities.

You'll build and maintain cloud infrastructure on AWS, implement CI/CD pipelines, and contribute to data pipelines using Glue, Athena, and S3. Collaboration across engineering, security, and data teams is essential.