DevOps and Data Engineer

Position Overview

Proofpoint is seeking a DevOps and Data Engineer to join our Data Platform team. This is a hybrid role that 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. You will build and maintain the cloud infrastructure (AWS-first), CI/CD pipelines, and DevOps tooling that enable data engineering teams to ship high-quality data products faster and more safely. 

What You'll Do

• 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.

• 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.

• Collaborate with data engineers, data scientists, and security teams to translate requirements into scalable, automated infrastructure solutions.

What You Bring to the Team

Required

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

• 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).

Nice to Have

• Knowledge of data quality frameworks (Great Expectations, Deequ, or similar) and experience integrating them into CI/CD.

• Familiarity with open table formats (Apache Iceberg, Delta Lake) and lakehouse patterns.

• Background in cybersecurity, threat intelligence, or security-data analytics environments.