Senior React Engineer — Remote, Flexible Hours, Growth

Location: Cordoba, Argentina
Employment type: Full time
Reference: R14751

Senior DevOps and Data Engineer

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—you will own the reliability, automation, and delivery of the systems that power Proofpoint’s data pipelines and analytics capabilities.

About Us

Proofpoint is a global leader in human- and agent-centric cybersecurity. We protect how people, data, and AI agents connect across email, cloud, and collaboration tools. Over 80 of the Fortune 100, 10,000 large enterprises, and millions of smaller organizations trust Proofpoint to stop threats, prevent data loss, and build resilience across their people and AI workflows. Our mission is simple: safeguard the digital world and empower people to work securely and confidently. Join us in our pursuit to defend data and protect people.

How We Work

At Proofpoint you’ll be part of a global team that breaks barriers to redefine cybersecurity guided by our BRAVE core values:
• Bold in how we dream and innovate
• Responsive to feedback, challenges and opportunities
• Accountable for results and best in class outcomes
• Visionary in future focused problem-solving
• Exceptional in execution and impact

What You’ll Do

• Design, implement, and maintain CI/CD pipelines (GitHub Actions, Jenkins, or equivalent) 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.

What You Bring to the Team

Required

• 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.

Nice to Have

• Familiarity with real-time / streaming data processing using Apache Kafka, Amazon Kinesis, or Glue Streaming ETL.
• Knowledge of data quality frameworks (Great Expectations, Deequ, or similar) and experience integrating them into CI/CD.
• Familiarity with open tabl