Jobs / engineering
Data Engineer
Darktrace · The Hague
About the role
Darktrace is a global leader in AI for cybersecurity that keeps organizations ahead of the changing threat landscape every day. Founded in 2013, Darktrace provides the essential cybersecurity platform protecting nearly 10,000 organizations from unknown threats using its proprietary AI.
The Darktrace Active AI Security Platform™ delivers a proactive approach to cyber resilience to secure the business across the entire digital estate – from network to cloud to email. Breakthrough innovations from our R&D teams have resulted in over 200 patent applications filed. Darktrace’s platform and services are supported by over 2,400 employees around the world. To learn more, visit http://www.darktrace.com.


Job Description:
The Data Engineers at Darktrace help design and develop cloud-native data infrastructure that powers AI/ML models within Darktrace produts. They build scalable systems to collect, store, and process data, handling datasets with billions of rows, and supporting the full ML model lifecycle.
The position is part of the R&D team in The Hague, and you will be expected to work a minimum of 2 days a week in office.
What they look for
To succeed in this role, you’ll need a strong foundation in data engineering and cloud technologies, along with fluency in English and proficiency in Python. You should be able to demonstrate:
Hands-on experience with data pipelines (ETL/ELT) and workflow orchestration tools such as Apache Airflow,
Solid knowledge of SQL/NoSQL databases, data modeling, and schema design,
Familiarity with streaming technologies (e.g., Kafka), containerization (Docker, Kubernetes), and at least one major cloud platform - preferably Google Cloud
Exposure to big data frameworks (Spark, Beam), infrastructure-as-code tools (Terraform), and MLOps practices is a plus.
Beyond technical expertise, the role requires strong analytical and critical thinking skills, effective project management, and clear communication of technical findings. You should be results-oriented, collaborative, and adaptable, with a proactive approach to knowledge sharing and documentation. Curiosity and a willingness to learn new technologies will help you thrive in this dynamic environment.