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Proofpoint

Senior DevOps and Data Engineer

Proofpoint is hiring a Senior DevOps and Data Engineer. Level rates it ; you can apply on Proofpoint.

Level's read on this job

  • On Level's scale, this data engineer role is Little AI ●○○○: aI is not part of the work.
  • Tools and skills the posting cites include AWS, Terraform and GitHub Actions.
  • Level classifies it as a senior role.
  • Level lists 129 other open roles at Proofpoint.

AI in this role

Proofpoint is hiring a Senior DevOps and Data Engineer to own cloud infrastructure, CI/CD pipelines, and data platform reliability.

awsterraformgithub-actionsjenkinsaws-gluedatadog
ai-agentsdevopsdata-engineeringinfrastructure-as-codeci-cddataops

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

Position Overview

Proofpoint is seeking a Senior 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. At the same time, you will actively contribute to the design and operation of data pipelines using AWS Glue, Athena, and S3, bringing a strong operational mindset to data engineering. If you thrive at the boundary between platform and data, love automating toil, and care deeply about reliability and developer experience, this role is for you.

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 table formats (Apache Iceberg, Delta Lake) and lakehouse patterns.

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

  • AWS Certified DevOps Engineer – Professional, AWS Certified Data Engineer – Associate, or AWS Certified Solutions Architect certification.

  • Experience with cost optimization tooling (Infracost, AWS Cost Explorer dashboards, Athena query cost governance).

Why Proofpoint?

At Proofpoint, we believe that an exceptional career experience includes a comprehensive compensation and benefits package. Here are just a few reasons you’ll love working with us:

  • Competitive compensation

  • Comprehensive benefits

  • Career success on your terms

  • Flexible work environment

  • Annual wellness and community outreach days

  • Always on recognition for your contributions

  • Global collaboration and networking opportunities

 

Our Culture:

Our culture is rooted in values that inspire belonging, empower purpose and drive success-every day, for everyone.

We encourage applications from individuals of all backgrounds, experiences, and perspectives. If you need accommodation during the application or interview process, please reach out to accessibility@proofpoint.com.

 

How to Apply

Interested? Submit your application along with any supporting information- we can’t wait to hear from you!

How we rate this

Senior DevOps and Data Engineer at Proofpoint rates 0 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI agentsDevOpsData EngineeringInfrastructure As CodeCI/CDDataopsAWSTerraform

Also common in data engineer jobs at this level

Pay

Typical data engineer job
$149k

This posting doesn't list pay. Use the typical data engineer figure when pay comes up. See data engineer jobs

Questions you could be asked

  1. How do you decide when an AI agent can act on its own versus asking for approval first?
  2. Tell me about a project where devops was part of your work. What did you do?
  3. Tell me about a project where data engineering was part of your work. What did you do?
  4. Tell me about a project where infrastructure as code was part of your work. What did you do?
  5. Tell me about a project where ci/cd was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: AI agents, DevOps, Data Engineering, Infrastructure As Code, and CI/CD. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.

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