Senior DevOps & Data Engineer — Remote

C&S Informática S.A.; Buenos Aires; Remoto; ARS 139.086.000 - 200.903.000; Tempo pieno

Vantaggi offerti da questo lavoro

Competitive pay

Flexible work environment

Wellness days

Global collaboration

Descrizione del lavoro

Proofpoint in Argentina is seeking a Senior DevOps and Data Engineer to join our Data Platform team. This role focuses on building and maintaining cloud infrastructure on AWS, designing CI/CD pipelines, and empowering data engineers to ship reliable data products.

This hybrid role blends platform engineering with data ops, emphasizing automation, security, observability, and scalable pipelines. You will mentor peers and drive improvements across the data stack.

Competenze

• 5+ years of professional experience in DevOps, platform engineering, or SRE with at least 2 years hands-on data engineering.
• 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.

Mansioni

• 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 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, 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.

Conoscenze

DevOps/SRE

Data engineering

AWS services

IaC Terraform/CDK

CI/CD pipelines

Docker/Kubernetes

Observability

Communication

Strumenti

Terraform

AWS CDK

GitHub Actions

Jenkins

Kubernetes

Docker

Airflow

MWAA

Descrizione del lavoro

Proofpoint in Argentina is seeking a Senior DevOps and Data Engineer to join our Data Platform team. This role focuses on building and maintaining cloud infrastructure on AWS, designing CI/CD pipelines, and empowering data engineers to ship reliable data products.

This hybrid role blends platform engineering with data ops, emphasizing automation, security, observability, and scalable pipelines. You will mentor peers and drive improvements across the data stack.