Zscaler is an AI-forward enterprise focused on digital transformation and cybersecurity. They are seeking an Information Security Engineer (Data Security) to lead their data security program, ensuring the protection of sensitive data across products and services while collaborating with various teams to implement security standards and practices.
Responsibilities:
- Own and evolve the end-to-end data security program architecture — including administration, configuration, and ongoing maintenance of data flow mapping and code-level scanning tools (e.g., Relyance.ai, BigID, Securiti.ai, OneTrust, or equivalent), data element mapping, and source code scanning pipelines and delivering continuous sensitive data visibility across Zscaler's product and service landscape
- Build and maintain the authoritative PII and sensitive data inventory covering service data flows and third-party egress; define and enforce data classification standards that engineering teams adopt during design and development, partnering with Privacy and Legal on regulatory alignment
- Lead POCs and technical evaluations for emerging data security capabilities — including DSPM controls, AI data governance tooling and privacy-enhancing technologies — translating findings into actionable build-vs-buy recommendations for leadership
- Drive shift-left adoption across product engineering teams by embedding data security reviews into the SDLC, running enablement sessions, and serving as the subject matter expert for teams building features that handle sensitive or regulated data including AI and LLM workloads processing PII
- Own data security control evidence for SOC 2, FedRAMP, and ISO audit cycles; maintain data flow documentation and third-party data sharing records that satisfy auditor requirements and support enterprise customer security reviews
Requirements:
- Foundational understanding of AI/ML technologies and experience leveraging, securing, or positioning AI-driven solutions to optimize outcomes within your functional domain
- Demonstrated curiosity and active exploration of tools, with a proven history of integrating new technologies to enhance daily workflows and augment problem-solving
- 5+ years in data security, privacy engineering, or a closely related discipline with hands-on experience owning a data security or data governance program, not just contributing to one
- Production experience administering and operating data flow mapping or data discovery tooling (e.g., Relyance.ai, BigID, Securiti.ai, OneTrust, Varonis, or equivalent) — including configuration, data element mapping, and ongoing platform maintenance
- Strong working knowledge of data classification frameworks, PII taxonomy, and sensitive data handling requirements across at least one major regulatory regime (GDPR, CCPA, HIPAA, or equivalent)
- Demonstrated ability to drive cross-functional adoption — experience partnering with engineering teams to embed data security practices into the SDLC, including running enablement sessions or defining data handling standards that developers actually follow
- Hands-on experience governing data flows in AI and LLM workloads — including PII exposure risk in RAG pipelines, training data classification, or sensitive data controls for fine-tuning workstreams — with the ability to define a data governance model for agentic and AI-driven product features
- Experience operating a DSPM program end-to-end — including policy design, tuning, incident triage, and metrics reporting — across cloud-native or SaaS environments at scale