Data Engineering Manager

Dragos, Inc.; United States; On-site; USD 150,000 - 190,000; Full time

Benefits offered by this job

Competitive equity package

Job summary

Dragos, Inc. is seeking a Data Engineering Manager to lead a team building the core data layer for our cybersecurity products. You will influence analytics, asset, and vulnerability engineering teams, guiding data models, schemas, and analytics architecture.

The role requires deep distributed data systems expertise, strong leadership, and a track record of developing high-performing teams in a cybersecurity or SOC context. Remote-first, with collaboration across North America, Europe, and APAC.

Qualifications

• 7+ years of engineering management experience
• Management experience with Agile and cross-functional Product Teams
• Cybersecurity or SOC experience with threat/asset intelligence domains
• Strong technical background in distributed data systems
• Hands-on with Elastic Stack, Airflow, Docker, Kubernetes, PostgreSQL, ClickHouse, dbt
• Rust experience strongly preferred
• Hands-on with AI-assisted development tools and workflows
• Comfortable with hands-on development or troubleshooting

Responsibilities

• Lead and mentor a team of data engineers, driving their technical growth and professional development
• Drive hiring and team growth to scale with roadmap demands
• Own the technical strategy and roadmap for the data platform, driving modernization initiatives
• Collaborate with product and engineering teams to define data models, schemas, and analytics architecture
• Partner with detection engineering and security stakeholders to ensure data quality and reliability
• Establish and drive engineering best practices, coding standards, and performance optimization
• Champion the adoption of AI-assisted development tools and workflows
• Provide guidance during software design, development, testing, and release
• Ensure timely delivery of projects, balancing technical debt and innovation
• Own production support for fielded deployments, including incident response and on-call coverage
• Foster a strong technical community by developing relationships among Engineering Managers
• Stay current with emerging data technologies and best practices

Skills

Distributed data systems

Team leadership

Agile & cross-functional teams

Data platform design

Tools

Elastic Stack

Airflow

Docker

Kubernetes

PostgreSQL

ClickHouse

dbt

Job description

At Dragos, the mission is personal. The systems we protect deliver the water you drink, power your home, and keep the hospitals your community depends on running. Those critical infrastructure systems that power our civilization around the world are under attack every day by adversaries. When those systems fail, people are immediately at risk. We are the global leader in xOT cybersecurity, combining technology, threat intelligence, and expert services. The people here chose this work because they understand what is at stake . Here, you will find a remote-first mission-driven team across North America, Europe, the Middle East, and APAC built on authenticity, transparency, and trust. If safeguarding the systems that protect your family, friends, and community is the kind of work that matters to you, you are in the right place.

About the Role

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. The ideal candidate has deep technical knowledge of distributed data systems, exceptional leadership skills, and a proven ability to develop high-performing teams, grounded in real cybersecurity or SOC domain experience. 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.

Responsibilities

• Lead and mentor a team of data engineers, driving their technical growth and professional development.
• Drive hiring and team growth to scale with roadmap demands.
• 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.
• Establish and drive engineering best practices, coding standards, and performance optimization strategies for data pipelines and storage systems.
• Champion the adoption of AI-assisted development tools and workflows across the team to accelerate delivery and improve code quality.
• Provide guidance during software design, development, testing, and release.
• Ensure timely delivery of projects, balancing technical debt and innovation.
• Own production support for fielded deployments, including incident response and on-call coverage for the data platform.
• Foster a strong technical community by developing close relationships amongst Engineering Managers.
• Stay current with emerging data technologies, frameworks, and best practices to drive continuous improvement.

Qualifications

• 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 IC/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
• Heavy hands‑on familiarity with AI-assisted development tools and workflows (e.g., LLM‑based coding assistants, AI‑driven data tooling), with a track record of driving adoption across a team
• Comfortable with hands‑on development or troubleshooting
• Excellent communication, leadership, and presentation skills

Compensation

• Competitive Equity Package

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