Data security platform for discovering, classifying, and protecting sensitive data
DataStealth builds a data-centric security platform designed to protect sensitive information from insider threats and external compromise. The stack—AWS (EKS, ECS, Lambda, DynamoDB), GCP, Azure, plus masking and tokenization capabilities—reflects a multi-cloud, infrastructure-heavy approach. Active projects signal architectural modernization (monolith refactoring, next-gen platform blueprint, AWS platform-scale design) alongside core security features, while hiring leans heavily toward senior engineering and leadership roles, suggesting both technical debt remediation and product maturation.
Notable leadership hires: Technical Engagement Lead
DataStealth is a data security platform operating in the 51–200 employee range, headquartered in Mississauga, Ontario. The platform discovers, classifies, and protects sensitive data and documents across enterprises, with specialties in data masking, tokenization, encryption, and compliance (PCI, privacy regulations). The company targets organizations managing complex data governance and cloud transformation, where protecting critical data without degrading performance is a key operational friction. Current roadmap emphasizes modernizing legacy monolithic systems, scaling AWS infrastructure, and expanding integrations alongside core masking and encryption capabilities.
DataStealth runs on AWS (EKS, ECS, Lambda, DynamoDB), Google Cloud Platform, and Azure, enabling multi-cloud data security deployments.
Yes. Engineering roles dominate the hiring mix (4 of 7 active roles), with seniority skewed toward senior and lead positions, plus a VP-level hire. All hiring is in Canada.
The platform provides data masking, tokenization, encryption, attribute-based access control, and dynamic data masking (DDM) for test data management and compliance audit scope reduction.
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