Senior DevOps & Data Engineer — AWS Data Platform

Darwoft; Buenos Aires; Hybride; ARS 1 800 000 - 3 000 000; Plein temps

Avantages offerts par ce poste

Competitive compensation

Comprehensive benefits

Flexible work environment

Annual wellness days

Global collaboration and networking

Résumé du poste

Proofpoint is seeking a Senior DevOps and Data Engineer to join our Data Platform team in a hybrid role. You will own reliability, automation, and delivery of data pipelines and analytics capabilities across AWS, building CI/CD pipelines and data infrastructure.

You will design and operate data workflows with AWS Glue, Athena, and S3, and contribute to observability, security, and governance. Strong collaboration with data engineers, data scientists, and security 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.

Responsabilités

• 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.
• Design and operate workflow orchestration environments (Amazon MWAA / Apache Airflow, AWS Step Functions) including upgrades, scaling, and reliability hardening.
• 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.
• 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.

Description du poste

Proofpoint is seeking a Senior DevOps and Data Engineer to join our Data Platform team in a hybrid role. You will own reliability, automation, and delivery of data pipelines and analytics capabilities across AWS, building CI/CD pipelines and data infrastructure.

You will design and operate data workflows with AWS Glue, Athena, and S3, and contribute to observability, security, and governance. Strong collaboration with data engineers, data scientists, and security teams is essential.