AI & Data Platform Engineering Manager

Zscaler, Inc.; San Jose (CA); Hybrid; USD 164,000 - 205,000; Full time

Benefits offered by this job

Time off plans

Parental leave options

Retirement options

In-office perks

Job summary

Zscaler, Inc. seeks a technically strong Manager – AI & Data Platform Engineering to lead and evolve our enterprise data platform into an AI-ready data/knowledge backbone.

The role blends architecture, hands-on development, people leadership, and platform strategy in a hybrid Santa Clara, CA setting. You will shepherd data pipelines, knowledge graphs, and AI infrastructure, guiding teams across the US and India while defining service levels and enabling self-service for internal AI initiatives.

Qualifications

• Deep understanding of Generative AI architectures and enterprise knowledge systems.
• 10+ years in software/data engineering or related field.
• 3+ years leading engineering teams with strong people leadership.
• Strong hands-on Python and SQL, plus modern data platforms on cloud.

Responsibilities

• Lead a US/India data and AI engineering team across locations.
• Own the Data Platform and pipelines turning data into AI-ready assets.
• Translate platform strategy into roadmaps and quarterly plans.
• Run the platform as a product for internal users with SLAs and onboarding.
• Build automated operations and reusable frameworks for data quality and observability.

Skills

Generative AI architectures

RAG systems

Python

SQL

Data engineering

Distributed systems

Tools

Snowflake

dbt

Matillion

Databricks

BigQuery

Job description

Zscaler, Inc. seeks a technically strong Manager – AI & Data Platform Engineering to lead and evolve our enterprise data platform into an AI-ready data/knowledge backbone.

The role blends architecture, hands-on development, people leadership, and platform strategy in a hybrid Santa Clara, CA setting. You will shepherd data pipelines, knowledge graphs, and AI infrastructure, guiding teams across the US and India while defining service levels and enabling self-service for internal AI initiatives.