Senior Security Engineer, Data Infrastructure

Senior Security Engineer

We're seeking a Senior Security Engineer to lead the data security infrastructure at Grow Therapy. The ideal candidate will own the systems that classify, protect, and govern sensitive data, ensuring it's treated with the highest standards of security.

• Define Data Security Vision: Develop a clear, opinionated vision for Grow's data security infrastructure, addressing risks, defining "secure by default," and setting a roadmap for achieving it.
• Build Automated Pipelines: Create automated classification and tagging pipelines that scan production data models, infer sensitivity, and propagate these tags through data lineage, aligning with our Data Classification Policy.
• Control Data Usage: Implement field-level dynamic masking, tokenization, and redaction driven by classification tags, ensuring sensitive data is exposed only when necessary and access is scoped and logged.
• Secure AI Tooling: Secure data connectors and pipelines feeding AI tools, including authentication, authorization, and observability, ensuring safety and appropriateness in the adoption of new AI technologies.
• Design Encryption Infrastructure: Design and ship encryption pipelines that protect our most sensitive data, including application-layer and field-level encryption, envelope encryption, and key management, making the secure path the default.

About the Role

Grow Therapy is a three-sided marketplace that empowers providers, augments insurance payors, and serves patients. Founded in February 2021, we've grown to empower over ten thousand therapists and millions of clients across the country and insurance landscape. We've raised over $328 million in funding and are valued at $3 billion.

Responsibilities

• Define Data Security Vision: Develop a clear, opinionated vision for Grow's data security infrastructure, addressing risks, defining "secure by default," and setting a roadmap for achieving it.
• Build Automated Pipelines: Create automated classification and tagging pipelines that scan production data models, infer sensitivity, and propagate these tags through data lineage, aligning with our Data Classification Policy.
• Control Data Usage: Implement field-level dynamic masking, tokenization, and redaction driven by classification tags, ensuring sensitive data is exposed only when necessary and access is scoped and logged.
• Secure AI Tooling: Secure data connectors and pipelines feeding AI tools, including authentication, authorization, and observability, ensuring safety and appropriateness in the adoption of new AI technologies.
• Design Encryption Infrastructure: Design and ship encryption pipelines that protect our most sensitive data, including application-layer and field-level encryption, envelope encryption, and key management, making the secure path the default.

Requirements

• Hands-on data infrastructure engineering experience
• Deep expertise in data security, data classification, masking/tokenization, encryption, and key management
• Comfortable writing production code, designing data pipelines and services, and conducting system design reviews
• Ability to set direction and execute on it, prioritizing high-leverage controls
• Clear, compelling communication skills to explain data-security tradeoffs and risk to non-technical audiences

Qualifications

• Experience with data security and infrastructure
• Strong understanding of data classification, masking/tokenization, encryption, and key management
• Proven ability to design and implement secure data protection solutions
• Experience with automated classification and tagging pipelines
• Knowledge of secure data access and usage policies
• Experience with secure data connectors and pipelines for AI tools
• Experience with encryption infrastructure for sensitive data

Skills

• Data security and infrastructure
• Data classification, masking/tokenization, encryption, and key management
• Automated classification and tagging pipelines
• Secure data access and usage policies
• Secure data connectors and pipelines for AI tools
• Encryption infrastructure for sensitive data

Benefits

• Comprehensive health coverage
• Parental leave and family support
• Financial wellness programs
• Flexible PTO and paid holidays
• Mental and physical health support
• Personal and professional development opportunities
• Wellness and development stipends
• Pet insurance discounts
• Commuter benefits
• Global travel assistance

Pay

The base compensation range for this position is: Hybrid Commitment: $182,000- $250,000 USD Annually
Fully Remote Commitment: $152,000–$208,000 USD Annually

Schedule

This role can be hybrid (onsite from our NYC, San Francisco, or Seattle hub location three days per week: Tuesday, Wednesday, Thursday) or fully remote. Both arrangements include travel 2–3 times per year (e.g., company and department offsites).