> Markdown version of [/jobs/ext/3844748-principal-software-engineer-data-platform-prisma-airs](https://www.wearedevelopers.com/jobs/ext/3844748-principal-software-engineer-data-platform-prisma-airs). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Principal Software Engineer (Data Platform Prisma AIRS) - **Company:** Palo Alto Networks - **Location:** Santa Clara, CA, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Big Data, BigQuery, Computer Programming, Directed Acyclic Graph (Directed Graphs), Data Infrastructure, Distributed Systems, Fault Tolerance, Data Flow Control, Python (Programming Language), Machine Learning, Open Source Technology, Reliability Engineering, Cloud Services, Security Software, Data Processing, Multi-Agent Systems, Apache Spark, Backend, Agentic-AI, Kubernetes, Information Technology, Apache Kafka, Terraform, Apache Beam, Golang - **Published:** October 20, 2026 - **Apply:** https://www.juju.com/job/23_836BB8FA99895F014C7F0C0ABFCBCE11 ## About the Role Bachelor's degree in Computer Science or a related field with 10+ years of relevant industry experience, or a Master's degree with 8+ years of experience. Deep domain expertise in designing, building, and operating highly scalable, fault-tolerant distributed systems, with exceptional programming skills in Golang and Python. Hands-on experience building backend data platform infrastructure using distributed execution engines such as Apache Beam or Apache Spark. Hands-on experience architecting, building, or deploying complex agentic workflows, tool-use pipelines, or multi-agent orchestrations within data infrastructure. Proven track record of profiling, benchmarking, and tuning high-throughput distributed pipelines to improve latency and resource efficiency. Broad experience with cloud-native data stacks (GCP/Dataflow preferred), messaging (Pub/Sub, Kafka), storage engines (BigQuery, Iceberg), and infrastructure tooling (Kubernetes, Terraform). Demonstrated ability to drive consensus across multi-team boundaries, solve complex technical problems, and mentor senior engineering talent. Preferred Qualifications Active contributions or committer status in open-source big data projects (Apache Beam, Spark, Airflow, Iceberg, etc.). ## Description 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 As a Principal Software Engineer, Data Platform on the Prisma AIRS Runtime Security team, you will serve as a technical visionary and strategic leader shaping the future of our enterprise data infrastructure. You will partner with executive leadership, product management, ML engineers, data scientists, and cross-functional software teams to conceptualize, architect, and deliver cutting-edge, enterprise-grade distributed processing solutions. You will be at the vanguard of innovation for our platform in the rapidly evolving space of real-time streaming and high-throughput batch data processing. Your responsibilities will transcend traditional pipeline development to lead continuous performance and efficiency optimizations, enabling multi-source data ingestion and transformation to power AI model lifecycle workflows, operational analytics, and automated security policy recommendations. You will drive technical excellence across the organization, set architectural standards, and act as a force multiplier by mentoring other engineers on the team. Key Responsibilities Partner with Product Management, SRE, ML Engineering, Security Researchers, and Quality Engineering to design and deliver high-throughput data platform capabilities and streaming services. Architect and build resilient, multi-source batch and streaming engines to power analytical workflows, business insights, and internal feature improvements. Profile, benchmark, and tune distributed execution DAGs, state storage, and compute resources to maximize throughput, lower processing latency, and optimize cloud expenditure at scale. Evangelize and implement modern software engineering best practices, including spec-driven development, comprehensive testing frameworks, and agentic coding workflows. Act as a force multiplier by mentoring senior and junior engineers, conducting rigorous architectural reviews, and cultivating a culture of technical excellence across the team.