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:
You will be joining the Data Engineering Community that specializes in data pipeline and structure design within a matrix-style organization. This community serves as the connective tissue for aligning data strategy, sharing best practices, and accelerating innovation across diverse product-focused initiatives.
Responsibilities:
- Create sustainable data contracts that address data governance requirements.
- Model complex data sources into performant analytics.
- Create and manage a data transformation layer that can become a core part of our analytic process.
- Collaborate with product engineering teams to deliver data solutions that enhance customer-facing products.
- Establish and contribute to shared tooling for observability, lineage tracking, and configuration validation.
Qualifications:
- 5+ years of data engineering experience.
- Experience with dimensional modeling and working with incremental data models.
- Skilled in implementing data observability frameworks, designing robust data contracts, and optimizing data structures for performance and scalability.
- Software development skills in Go, JVM-family, Python, and/or Node.js languages with cloud-native architectures.
- Experience manipulating, processing, and extracting value from medium-to-large scale datasets, especially relevant if cybersecurity or industrial data.
- Knowledge of integrating cloud and on-premises technologies in industrial environments, with deployments on Kubernetes and Docker.
- Experience with message queuing, stream processing on deployable infrastructure.
- Detailed domain familiarity and prior experience in at least one data-heavy field / product market segment, especially relevant if knowledgeable in cybersecurity threat detections, threat intelligence, or ICS/OT operations.
