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# Senior Security Engineer, Data Security

- **Company:** Kikoff Inc.
- **Location:** San Francisco, CA, United States
- **Experience:** Expert
- **Salary:** $268,000 - $321,000
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Amazon S3, Application Services, Audit Trail, Cloud Storage, Databases, Data Mapping, Data Security, Data Warehousing, Relational Databases, Identity and Access Management, Python (Programming Language), Key Management, Role-Based Access Control, Ruby, Data Streaming, Tokenization, Privacy Controls, Pulumi, Data Processing, Large Language Models, Snowflake, Amazon Virtual Private Cloud (VPC), Agentic-AI, Terraform, Golang
- **Published:** November 7, 2026
- **Apply:** https://www.juju.com/job/28_25304_62ea808b7dc050a508aac09e1aa36d55

## About the Role

This is a consumer fintech startup, and you will be working with serial entrepreneurs who have built strong consumer brands and innovative products. We value extreme ownership, clear communication, a strong sense of craftsmanship, and the desire to create lasting work and work relationships. Yes, you can build an exciting business AND have real-life real-customer impact., * 6+ years in security engineering with deep, hands-on data security experience: encryption, tokenization, access control design, key management

 * Strong command of AWS security primitives (IAM, KMS, S3 security, VPC controls)
 * Experience securing a modern data stack: Snowflake or a comparable warehouse, plus relational databases in production
 * You\'ve designed and shipped access control systems, not just configured them. Row/column-level security, ABAC/RBAC, access brokering
 * Fluency in at least one language for automation (Python, Go, Ruby, or similar)
 * Comfortable in a regulated environment
 * Hands-on with infrastructure-as-code (Terraform or Pulumi)

## Description

* Own the data security roadmap end to end: classification, access controls, encryption, tokenization, and data flow security across AWS, Snowflake, and our internal pipelines.
 * Set the strategy for how humans, services, and AI agents access sensitive data. You decide what good looks like and build towards it.
 * Drive least-privilege access at scale, including brokered access patterns for our data warehouse and production databases rather than standing credentials.

Build & Secure

 * Design and ship tokenization and field-level protection for our most sensitive data
 * Build column-level and role-based access controls across Snowflake and RDS, with audit visibility into who touched what and why
 * Secure data flows between cloud storage, pipelines, and application services so the secure path is the default path
 * Define and enforce access controls for AI agents to guarantee least privilege permissions and proper audibility.

Prove It

 * Build audit logging and data access monitoring that holds up in front of auditors and regulators, not just dashboards
 * Support data mapping and privacy engineering work for new markets and regulatory regimes (GLBA, LGPD, state privacy laws)
 * Partner with Legal and Compliance on data handling requirements, and translate them into infrastructure, not policy docs

Enable Engineering

 * Give engineers paved roads for handling sensitive data: reusable patterns, clear guidance, fast answers
 * Threat model new data flows before they ship, not after, * Experience securing data access for AI/LLM systems and agentic workloads
 * Tokenization at scale in fintech or payments
 * Audit logging and data access monitoring you built yourself, not bought
 * Privacy engineering depth: data mapping, retention, deletion pipelines, cross-border transfer controls
 * Consumer fintech or financial services background