Palo Alto Networks
Principal Product Manager — Logging & Streaming Data Platform
$177K–$286K
Office - USA - CA - Headquarters · No · Principal · Full-time · Posted Oct 22, 2026
- Experience
- 12+ years of progressive product management experience.
- Education
- Bachelor’s degree in Computer Science, Electrical Engineering, Data Science, or equivalent technical practical experience; Master’s or MBA preferred.
- Visa sponsorship
- Will not sponsor applicants for work visas for this position.
About the job
Leads the vision, architecture strategy, and roadmap for Palo Alto Networks’ logging and streaming data platform, enabling scalable security analytics and AI-driven operations.
What you'll do
- Set platform strategy and lead architectural tradeoffs for large-scale logging, telemetry ingestion, streaming, and data storage.
- Align platform capabilities across product lines and advise enterprise customers and executives on requirements and outcomes.
- Define data governance, unit economics, KPIs, and data-pipeline capabilities for AI/ML security workflows.
What they ask for
- 12+ years of progressive product management experience leading high-scale enterprise cloud platforms, SaaS infrastructure, or distributed systems.
- Demonstrated success leading exabyte-scale logging, observability, SIEM, streaming data pipelines, or security data lake platforms.
- Expertise in distributed systems, real-time streaming, storage tiering, data lakes, API-first strategies, cloud unit economics, and SaaS margin optimization.
- Bachelor’s degree in Computer Science, Electrical Engineering, Data Science, or equivalent technical practical experience.
Nice to have
- Strategic background in network security, NGFW, SASE, or enterprise SecOps.
- Familiarity with Apache Kafka, Flink, Pulsar, Iceberg, Delta Lake, Snowflake, or BigQuery.
Pay
$176,800.00 - $286,000.00/yr (USD, annual base salary)
Tools
Apache Kafka, Flink, Pulsar, Iceberg, Delta Lake, Snowflake, BigQuery
AI focus
Architect data pipelines for AI/ML security workflows, real-time automation, predictive analytics, LLM training, and AI inferencing.
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