Information Security Engineer (Data Security)

Zscaler•San Jose, TX

2d•Hybrid

About The Position

Zscaler accelerates digital transformation to ensure our customers can be more agile, efficient, resilient, and secure. As an AI-forward enterprise, we are constantly pushing the envelope, leveraging the world’s largest security data lake to power our cloud-native Zero Trust Exchange platform. This innovation protects our customers from cyberattacks and data loss by securely connecting users, devices, and applications in any location. We seek innovators who actively use AI to amplify their impact and who thrive in an environment where we leverage intelligent systems to stay ahead of evolving threats. We believe in transparency and value constructive, honest debate —we’re focused on getting to the best ideas, faster. We build high-performing teams that can make an impact quickly and with high quality. To do this, we are building a culture of execution centered on customer obsession, collaboration, ownership, and accountability. We value high-impact, high-accountability with a sense of urgency where you’re enabled to do your best work and embrace your potential. If you’re driven by purpose, thrive on solving complex challenges, and want to be part of the team that’s helping to secure the AI age, we invite you to bring your talents to Zscaler and help shape the future of cybersecurity. We are looking for an Information Security Engineer (Data Security) to join our team. This is a Hybrid role (onsite three days a week in San Jose, CA or another Zscaler office; remote can be considered for exceptional candidates), reporting to the Director, Information Security Compliance in the Information Security Compliance department. The Information Security Engineer (Data Security) will be the technical owner of Zscaler's shift-left data security program, responsible for building and maintaining continuous visibility into how sensitive data moves across products, services, and third parties. You will anchor data classification governance, DSPM operations, and audit control evidence; serving as the connective tissue between Product Security, Engineering, Privacy, and Compliance. As AI workloads expand, you will become the critical data risk layer ensuring PII and sensitive data is governed across AI systems, fine-tuning workstreams, and third-party egress.

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

Nice To Haves

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

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