Distinguished Software Engineer (DLP - Big Data & AI )

Company Description

Our Mission

At Palo Alto Networks® everything starts and ends with our mission:

Being the cybersecurity partner of choice, protecting our digital way of life.
Our vision is a world where each day is safer and more secure than the one before. We are a company built on the foundation of challenging and disrupting the way things are done, and we’re looking for innovators who are as committed to shaping the future of cybersecurity as we are.

Who We Are

We believe collaboration thrives in person. That’s why most of our teams work from the office full time, with flexibility when it’s needed. This model supports real-time problem-solving, stronger relationships, and the kind of precision that drives great outcomes.

Job Description

At Palo Alto Networks, we are redefining cybersecurity. As a Distinguished Engineer on the Enterprise DLP team, you will be the foremost technical leader responsible for architecting and scaling the data platform that underpins our industry-leading cloud-delivered DLP service. Your mission is to establish the standards and systems necessary to process and analyze massive volumes of sensitive data, leveraging cutting-edge AI/ML, to ensure our customers' data remains protected across all network, cloud, and user vectors.

Your Impact & Responsibilities

As a Distinguished Engineer, you will own the long-term technical direction and execution for all data and analytics infrastructure within Enterprise DLP.

I. Architecture & Strategic Vision

• Define Architectural Roadmap: Set the 3-5 year technical strategy and architectural vision for the Enterprise DLP data platform, emphasizing scalability, performance, security, and cost-efficiency.
• Big Data & AI Foundation: Drive the design, implementation, scaling, and evangelism of the core BigQuery, Vertex AI, Nvidia Triton, Kubeflow platform components that enable high-velocity data ingestion, transformation, and Machine Learning model serving for DLP detections.
• Real-time Decisioning: Architect and implement ultra-low latency data ingestion and processing systems (utilizing Kafka, Pub/Sub, Dataflow) to enable real-time DLP policy enforcement and alert generation at massive enterprise scale.
• Cross-Functional Influence: Act as the technical voice of the DLP data platform, collaborating with Engineering VPs, Product Management, and Data Science teams to align platform capabilities with product innovation.
• Detection Algorithm Enablement: Architect the core data structures and serving layers that enable high-performance DLP classification, like Regex, Exact Data Matching (EDM), Document Fingerprinting, and advanced ML/AI classifiers.

II. High-Scale Data Platform Engineering

• Big Data Pipeline Mastery: Architect and Lead the design and implementation of highly resilient, optimized batch and real-time data pipelines (ETL/ELT) to transform raw data streams into high-quality, actionable datasets.
• Optimized Datasets: Expertly design and optimize clean, well-structured analytical datasets within BigQuery, focusing on partitioning, clustering, and schema evolution to maximize query performance for both operational analytics and complex data science/ML feature generation.
• Database Strategy: Provide deep, hands-on expertise in both SQL and NoSQL databases like MongoDB, Spanner, BigQuery, advising on the optimal data persistence layer for diverse DLP data use cases (e.g., policy configurations, high-speed telemetry, analytical fact tables).
• MLOps Implementation: Establish robust MLOps practices model deployment & execution pipelines like Vertex AI, Nvidia Triton for DLP models, including automated pipelines for continuous training, versioning, deployment, and monitoring of model drift.
• Performance Engineering: Debug, optimize, and tune the most challenging performance bottlenecks across the entire data platform, from initial data ingestion to final analytics query execution, often dealing with PBs of data.

III. Mentorship & Operational Excellence

• Technical Mentorship: Mentor and develop Principal and Staff-level engineers, raising the bar for engineering craftsmanship and data platform development across the organization.
• Operational Health: Define and implement advanced observability, monitoring, and alerting strategies to ensure the end-to-end health and SLOs of the mission-critical DLP data service.

Qualifications

Your Experience 

• 12+ years of experience in a high-scale data-inten