Key skills
Cybersecurity conceptsVulnerability managementExposure managementThreat managementCybersecurity data pipelinesSIEMVulnerability Management platformsData ingestionData mappingData deduplicationData normalizationData unificationSecurity tools integrationEDRVM scannersCNAPPCSPMTicketing systemsCMDBIdentity managementCloud logsPythonSQLData analysisData modelingData parsingData transformationsAPI interactionAI/ML technologiesAIMLClaudeGeminiCollaborationSales
About this role
Zscaler is an AI-forward enterprise focused on accelerating digital transformation and enhancing cybersecurity. The Principal Software Development Engineer will be responsible for connecting and onboarding diverse cybersecurity data sources, ensuring data quality, and collaborating with various teams to meet customer needs.
Responsibilities:
- Master the Zscaler SecOps platform and partner cross-functionally with Sales, Product, and Services to translate customer requirements into actionable integration plans
- Onboard and map diverse cybersecurity and IT data sources in collaboration with subject matter experts (SMEs) to align directly with customer use cases
- Own data quality and pipeline integrity by auditing environments, proactively troubleshooting issues, identifying security gaps, and defining clear remediation steps for customers
- Leverage Python, APIs, and AI coding agents (such as Claude Code or Gemini CLI) to efficiently configure, customize, and automate data transformations and platform workflows
- Communicate technical findings to stakeholders and deliver field-based insights to the Engineering team to drive continuous product improvements
Requirements:
- Strong engineering background combined with a broad understanding of cybersecurity concepts, specifically vulnerability, exposure, and threat management
- Hands-on experience managing cybersecurity data pipelines (such as SIEM or Vulnerability Management platforms), including ingestion, mapping, deduplication, normalization, and unification
- Proven track record integrating security tools and data sources, including EDR, VM scanners, CNAPP/CSPM, ticketing/CMDB, identity, and cloud logs
- Proficiency in Python and SQL for data analysis, modeling, parsing, transformations, API interaction, automation, and end-to-end troubleshooting
- Foundational knowledge of AI/ML technologies with experience leveraging, securing, or positioning AI-driven solutions to optimize functional outcomes
- Bachelor's degree in Computer Science, Information Technology, or equivalent professional experience
- Excellent problem-solving abilities and a high level of attention to detail
- Direct experience working with data transformation pipelines