Senior Engineer (Sr. Data Security Analyst)

TL;DR

Senior Engineer (Sr. Data Security Analyst) (Cybersecurity): Identifying, assessing, and mitigating data-related risks across cloud and on-prem environments with an accent on data classification, access controls, and DLP implementation. Focus on leveraging AI/ML analytics for anomaly detection, predictive risk modeling, and optimizing security tools to prevent data exfiltration and enhance threat response.

Location: Fully remote in the USA. Candidates near CB offices can opt for hybrid (Tuesday and Wednesday in office). Must be authorized to work in the United States.

Salary: $153,000 - $166,000

Company

Self-sustaining nonprofit advancing educational opportunities through assessments like Digital SAT and AP exams.

What you will do

• Define and implement data classification, handling, and access control policies using analytics to address threats.
• Configure and tune DLP, DSPM, CASB, and cloud security controls with ML to detect sensitive data exfiltration.
• Map and inventory sensitive data, support automated tagging, and provide expertise on encryption and tokenization.
• Monitor alerts, triage events, and assist investigations using behavioral analytics and AI agents.
• Collaborate with Legal, Privacy, and Data Governance on compliance and deliver data security reporting with KPIs.

Requirements

• 5+ years in data security, cybersecurity, or information protection in mid- to large-scale environments
• Proven AI/ML or advanced analytics for risk detection and automation (Python preferred)
• Hands-on with data protection tools for discovery, classification, and analytics
• Knowledge of security principles: data classification, access control, encryption, privacy-by-design
• Experience with AWS/Azure data flows, SIEM, endpoint tools, and behavioral analysis
• Authorized to work in the United States

Culture & Benefits

• Inclusive environment valuing diverse backgrounds and mission-driven work.
• Comprehensive compensation package adjusted by location, experience, and market data.
• Support for emerging technologies, AI solutions, and continuous learning.
• Emphasis on candid feedback, learner orientation, problem-solving, and collaboration.

Hiring process

• Resume review, recruiter screen, hiring manager interview, performance exercise (e.g., live coding), panel interview, leadership conversation, and reference checks.
• Applications reviewed immediately until position filled.