Data Engineer, Security

Responsibilities

• Data Modeling & Architecture: Design and implement robust star schema models within a medallion architecture (Bronze/Silver/Gold) to support cyber insurance and cybersecurity analytics.
• Pipeline Engineering: Build scalable ELT pipelines using Snowflake and dbt, ensuring high data quality and observability.
• Monitoring & Observability: Define and implement critical SLIs for data freshness, volume, and schema integrity. Build automated alerting to ensure SLOs are met.
• BI Enablement: Develop and maintain the LookML semantic layer for business stakeholders.
• Security & Compliance: Implement data masking, RBAC, and secure data-handling practices.
• Engineering Excellence & Mentorship: Serve as a technical peer by participating in code reviews and sharing dbt and Python best practices.
• AI Integration: Build feature stores and data foundations for AI-driven risk scoring and automated underwriting.

Requirements and Qualifications

• Experience with Looker and LookML.
• Active use of Cursor or other AI-assisted coding environments.
• Prior experience in cybersecurity or cyber insurance.
• Experience building data foundations for AI agents.

Compensation and Benefits

• US base salary: $110,900–$163,350 per year, depending on geographic market and factors including education, skills, qualifications, experience, credentials, and location.
• 100% medical, dental, and vision coverage.
• Flexible paid time off.
• Annual home office stipend and WeWork access.
• Mental and physical health wellness programs.
• Competitive compensation and advancement opportunities.