Zscaler

Zscaler

Staff Product Manager - Data Protection

Remote - USA; Santa Clara, California, USA · Staff+ · Full-time

Sponsorship not specified$164k-$205kDetected 2 days ago
Machine LearningCybersecurityProduct ManagementSalesZero TrustResearchCommunicationCollaborationProblem Solving

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odds of building a lasting career here

64Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role100
Entry-level history0
PERM / green-card track0
Lottery odds (Level IV)94
Fits your clock70

Sponsors, but it's cap-subject — you still face the weighted lottery (~61% per draw at Level IV). Good if you win; have a cap-exempt backup on your list.

Lottery odds assume a STEM candidate.

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Employer immigration record

from this employer's Department of Labor filings

Green-card filing pattern in this occupation

Context, not a finding about this posting: of this employer's 48 green-card filings in this occupation, 100% were for a worker who already held the job.

Green-card follow-through: 75%

Of 28 labor certifications old enough to have been used, 7 expired without the employer filing the next step. Median time from filing to decision: 500 days.100% of their filings were for a worker who already held the job.Only certifications past the 180-day window are counted — recent ones cannot have expired yet.

Files H-1B transfers

44 transfer filings in the last year, covering 44 workers. Median labor-condition decision: 7 days. An employer that already files transfers is one that can take over an existing H-1B.

Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.

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About the role

  • We bring these commitments to life through three core behaviors: ownership and collaboration, trust through outcomes and impact, and a challenge culture with ongoing feedback.
  • Ready to make an impact at the company pioneering security transformation in the AI era?
  • This is a hybrid, based in San Jose, CA (3 days onsite) role, reporting to the Director, Product Management in the Product Management department.

Responsibilities

  • At Zscaler, we are committed to building a team that reflects the communities we serve and the customers we work with.
  • We strive to create a workplace where employees are treated with respect and have the chance to succeed.
  • Own the end-to-end product lifecycle for Data Security products, including Web DLP and Email DLP
  • Define, document, and prioritize product requirements using market research, competitive insights, and customer feedback
  • Partner with cross-functional teams (Engineering, UX, Support, Operations, Sales, Marketing) to take ideas from concept to successful delivery
  • Support product deployment and sales enablement across beta and production environments in collaboration with Support, Operations, and Sales teams
  • Drive and execute go-to-market plans with Marketing and Sales to ensure adoption and measurable product success
  • You're comfortable building the path as you walk it.
  • You thrive in a dynamic environment, seeing ambiguity not as a hindrance, but as the raw material to build something meaningful.
  • You love running towards the challenges because you are laser-focused on finding the solution, knowing that solving the hard problems delivers the biggest impact.

Compensation

  • $164,000 - $205,000 USD
  • Zscaler complies with all applicable federal, state, and local pay transparency rules.

Company info

  • Zscaler (NASDAQ: ZS) accelerates digital transformation so customers can be more agile, efficient, resilient, and secure.
  • The Zscaler Zero Trust Exchange platform protects thousands of customers from cyberattacks and data loss by securely connecting users, devices, and applications in any location.
  • Driven by deep customer obsession, we are committed to the mission, outcome, and to each other.

This listing is sourced directly from Zscaler's careers page and normalized into a canonical job model.