Staff Data Engineer

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 looking for a Staff Data Engineer to join our growing Data Platform team. In this senior individual-contributor role you will design, build, and operate the large-scale data infrastructure that underpins Proofpoint's cybersecurity products and analytics. You will work across the full data lifecycle—ingestion, transformation, orchestration, and delivery—using modern cloud-native tooling on AWS. You'll partner with data scientists, product engineers, and business stakeholders to turn raw data into reliable, governed, and performant data assets that drive product decisions and customer value.

What You'll Do

• Design and implement scalable, reliable data pipelines using AWS Glue (PySpark and Glue Studio) to ingest and transform petabyte-scale datasets stored in Amazon S3.

• Build and maintain our cloud data lake architecture on S3—defining partition strategies, file formats (Parquet, ORC, Delta), and data-catalog schemas in AWS Glue Data Catalog.

• Establish and enforce data quality standards—implement validation frameworks, anomaly detection, and SLA-driven alerting to ensure data reliability.

• Define and drive engineering best practices: code reviews, CI/CD for data pipelines, Infrastructure-as-Code (Terraform/CDK), and DataOps principles.

• Serve as a technical leader and mentor—conduct design reviews, guide junior engineers, and influence the team's technical roadmap.

• Collaborate closely with data scientists, ML engineers, and product managers to translate business requirements into robust data models and pipeline specifications.

• Champion data governance, lineage tracking, and privacy-by-design principles across all data assets.

• Troubleshoot and resolve production incidents, perform root-cause analysis, and drive preventive improvements.

• Contribute to architecture decision records (ADRs) and technical documentation.

What You Bring to the Team

Required

• 8+ years of professional software or data engineering experience, with at least 4 years focused on cloud data platforms.

• Deep expertise with AWS data services: S3 (lifecycle policies, event notifications, encryption), AWS Glue (ETL jobs, Crawlers, Data Catalog, Glue Studio), and Amazon Athena (query optimization, workgroups, federated queries).

• Strong Python programming skills; proficiency writing production-grade PySpark or Spark (Scala) for large-scale data transformation.

• Solid SQL fundamentals—ability to write and tune complex analytical queries.

• Excellent communication skills—able to present technical trade-offs clearly to both engineering and non-engineering stakeholders.

• Proven experience mentoring engineers and leading technical design discussions.

• Bachelor's degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience).

Nice to Have

• Experience with real-time / streaming data processing using Apache Kafka, Amazon Kinesis, or AWS Glue Streaming ETL.

• Familiarity with AWS Lake Formation for fine-grained access control and data governance.

• Knowledge of Amazon Redshift or other cloud data warehouses.

• Experience with data quality frameworks (Great Expectations, Deequ, or similar).

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

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

• Contributions to open-source data engineering projects or publications.

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 [email protected].

How to Apply

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