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.
- 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
- 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

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