Distinguished Software Engineer (Big Data & AI)

Our Mission At Palo Alto Networks®, we’re united by a shared mission—to protect our digital way of life. We thrive at the intersection of innovation and impact, solving real-world problems with cutting-edge technology and bold thinking. Here, everyone has a voice, and every idea counts. If you’re ready to do the most meaningful work of your career alongside people who are just as passionate as you are, you’re in the right place. Who We Are In order to be the cybersecurity partner of choice, we must trailblaze the path and shape the future of our industry. This is something our employees work at each day and is defined by our values: Disruption, Collaboration, Execution, Integrity, and Inclusion. We weave AI into the fabric of everything we do and use it to augment the impact every individual can have. If you are passionate about solving real-world problems and ideating beside the best and the brightest, we invite you to join us! 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 Summary The Team You’ll be working in a top tier cybersecurity company and collaborating with some of the brightest minds in technology. Our team doesn’t shy away from tackling big problems. You will help build and support the tools and infrastructure enabling our developers to release the products that our customers depend on to defend against cyberattacks. Joining this dynamic and fast-paced team will give you the opportunity and thrill of resolving the technical and process gaps that hold back productivity. Job Summary 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. Key Responsibilities As a Distinguished Engineer, you will own the long-term technical direction and execution for all data and analytics infrastructure within Saas Data Security and AI. 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 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 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 Required Qualifications 12+ years of experience in a high-scale data-intensive environment, with a minimum of 3+ years operating as a Distinguished or Principal-level Engineer/Architect Mastery of Google Cloud Platform (GCP) with extensive, hands-on experience architecting and scaling solutions using BigQuery and Vertex AI or equivalent AWS, Azure, or other Big Data & AI services Expertise in Big Data processing frameworks and managed services, specifically with building and scaling data and analytics pipelines using Dataflow, Pub/Sub, and GKE (or equivalent technologies like Apache Spark/Kafka) Strong experience in SQL & NoSQL databases (e.g., MongoDB, Cassandra, Spanner), with an understanding of their respective architectural trade-offs for distributed systems Demonstrated ability to design scalable data models and systems that enable high-pr