Data Engineering Manager

7+ years of engineering management experience, consistently building and leading highly effective teams

Management experience with Agile and working in cross-functional Product Teams

Cybersecurity or SOC (Security Operations Center) experience required with knowledge of threat detection, threat intelligence, vulnerability/asset intelligence, or ICS/OT security, given this role's direct influence on teams supporting those domains

Strong technical background in distributed data systems

Prior experience as an engineer with strong working knowledge of technologies such as the Elastic Stack, Airflow, Docker, Kubernetes, PostgreSQL, ClickHouse, and dbt

Rust experience strongly preferred

Salary: $220,000

Competitive Equity Package

Comprehensive Benefits Plan

#LI-NH1 #LI-REMOTE

Dragos is an Equal Opportunity Employer and considers applicants for employment without regard to race, color, religion, sex, orientation, national origin, age, disability, genetics, or any other basis forbidden under federal, state, or local laws. All new hires must pass a background check as a condition of employment.

We are looking for a Data Engineering Manager to lead a team of data engineers responsible for the core data layer underpinning our products, with direct influence on our analytics, asset, and vulnerability engineering teams, amongst others.

This role will also drive modernization efforts across the platform to improve performance and resource efficiency, and will champion the team's adoption of AI-assisted engineering practices.

Lead and mentor a team of data engineers, driving their technical growth and professional development.

Own the technical strategy and roadmap for the data platform, driving modernization initiatives that improve performance, scalability, and resource efficiency.

Collaborate with product and engineering teams to define data models, schemas, and analytics architecture across the teams this role influences.

Partner with detection engineering and other security stakeholders to ensure data quality, freshness, and reliability for threat-detection and analysis workflows.