Lead Data Security Engineer

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iFood

WebsiteLinkedInAll Job Openings

5001 - 10000 employees

🍽️ Food & Beverage

📦 Logistics

📣 Marketing

Food & Beverage • Logistics • Marketing

iFood is a leading food delivery platform based in Brazil, connecting customers with a wide array of restaurants and food options. The company leverages cutting-edge technology and artificial intelligence to improve customer experience, streamline operations, and enhance delivery logistics. iFood fosters a diverse and inclusive work environment, focusing on sustainability and the positive impact of its services on the community.

📋 Description

• Own the DLP (Data Loss Prevention) and ZTNA strategy for endpoints, cloud applications and communication channels. • Define and enforce data classification policies and handling procedures for internal users and third parties. • Manage and evolve security controls for corporate SaaS platforms, hardening configurations for Databricks, Salesforce, Google Workspace, Slack and similar tools. • Define and enforce Document Retention & Disposal policies, establishing retention periods, archival processes and secure disposal procedures in compliance with LGPD, GDPR and internal governance requirements. • Collaborate with the CSIRT and investigation teams during data exfiltration incidents, providing DLP insights and data context. • Monitor insider threat indicators and develop behavioral analytics rules to detect anomalous data access or movements. • Define and enforce device posture policies, ensuring only compliant devices access corporate systems (integration with ZTNA). • Analyze and assess the security architecture of data integrations between internal systems, partners and customers. • Identify risks in data exchange patterns — APIs, ETL pipelines and file transfers — and propose compensating controls. • Collaborate with engineering and data teams to embed security requirements into integration design (security by design). • Assess and improve data residency, encryption in transit and at rest, and access control models for production environments. • Support compliance requirements related to data protection (LGPD, GDPR, PCI-DSS) and regulatory requirements (BACEN, PCI, among others). • Lead Sensitive Data Mapping initiatives in corporate and production environments — identifying, cataloging and classifying sensitive data assets to ensure appropriate controls are applied across the data lifecycle. • Use AI to detect anomalous data patterns, automate classification, improve DLP policy tuning and accelerate investigations — with measurable impact on risk reduction. • Create and maintain metrics on data risk exposure, policy violations and remediation progress. • Act as a subject-matter expert and advisor to product, engineering and legal teams on data protection topics. • Take ownership: proactively surface risks, propose solutions and drive cross-functional outcomes independently.

🎯 Requirements

• Strong experience in data protection, DLP, ZTNA and information security governance. • Solid knowledge of Zero Trust architecture principles and practical implementation (ZTNA, conditional access and device posture). • Deep knowledge of security hardening for corporate SaaS (Google Workspace, Salesforce, Databricks or similar). • Knowledge of data architecture concepts: APIs, ETL pipelines, data warehouses and cloud data platforms. • Familiarity with regulatory frameworks: LGPD, GDPR and PCI-DSS. • Hands-on experience with AI tools for anomaly detection, data classification or security automation — with tangible, measurable results. • Strong analytical and investigative skills — ability to trace a data leak from initial signal to root cause. • Ability to make autonomous decisions: comfortable handling ambiguity and making risk-based decisions independently. • Ownership: proactive identification and escalation of risks, influencing stakeholders and driving outcomes beyond formal remit. • Leadership mindset: think about scalability, mentor others and be ready to evolve into a leadership role. • Advanced English (required).

🏖️ Benefits

• Experience with SASE platforms (Netskope, Zscaler or similar). • Experience with DSPM tools (Netskope, Cyera, Wiz or similar). • Experience in data engineering or analytics — understanding end-to-end data flows. • Certifications: CISM, CDPSE, CISSP or equivalent.