Sr. Staff Integration Engineer (Security Platform and Data Pipelines)

India · Bangalore · Posted Sep 22, 2026

At a glance

The Sr. Staff Integration Engineer will join the Technical Implementation and Integration department to connect and onboard diverse cybersecurity data sources.
This role focuses on mapping and normalizing security data to power exposure and threat management use cases while customizing workflows to deliver measurable outcomes.
The position requires technical depth, comfort with complex datasets, and the ability to communicate with both technical and non-technical stakeholders.

Quickly get up-to-speed on Zscaler’s SecOps platform, utilizing Python and APIs to configure, customize, and automate data transformations and workflows.
Partner with cybersecurity subject matter experts (SMEs) to onboard new data pipelines and map diverse IT and security sources to fulfill specific customer use cases.
Proactively troubleshoot pipeline health and audit customer data across environments to identify quality issues, flag security gaps, and define clear remediation steps.
Collaborate cross-functionally with Sales, Product, and Services teams to translate customer needs into actionable implementation and integration plans.
Communicate technical findings clearly to stakeholders and feed valuable, field-based insights back to Engineering to drive continuous product improvements.

Foundational understanding of AI/ML technologies and experience leveraging, securing, or positioning AI-driven solutions.
Hands-on experience managing the complete data pipeline lifecycle, including ingestion, mapping, deduplication, normalization, merging, and unification.
Specialized experience working with data pipelines within cybersecurity platforms (e.g., SIEM, Unified Vulnerability Management).
Broad understanding of vulnerability, exposure, and threat management.
Proven ability to integrate diverse security tools and data sources, such as EDR, vulnerability scanners, CNAPP/CSPM, ticketing systems/CMDB, identity providers, and cloud logs.
Strong proficiency in data modeling, SQL, and Python to handle data parsing, execute transformations, interact with APIs, and troubleshoot complex data issues.

Experience designing or optimizing security data pipelines that feed AI-driven anomaly detection models or automated threat-hunting systems.
Bachelor’s degree in Computer Science, Information Technology, or equivalent professional experience.
Excellent problem-solving abilities and a high level of attention to detail.