Data Engineer

Location: The Hague

Data Engineer
Build cloud-native data infrastructure powering AI/ML features for ASM

Location:

The Hague, South Holland, Netherlands

About

The Role
Darktrace Data Engineer Position
The Data Engineers at Darktrace help design and develop cloud-native data infrastructure that powers AI/ML models within the Darktrace / Attack Surface Management (ASM) product. 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 will I be doing:

Your work will lay the foundation for future product innovation and support the rollout of model-driven features in the ASM product by ensuring reliable data flows from source to model to production. You will help build a data backbone that is easily maintainable and extensible while upholding high standards for data quality, scalability, and cost efficiency.

You will work closely with Data Scientists, MLOps Engineers, and Software Engineers to ensure seamless integration between data infrastructure, ML workflows and the ASM backend. You'll contribute to architectural discussions and help implement robust, maintainable solutions aligned with data engineering best practices. Additionally, you will be responsible for:

Contributing to the design, implementation, and maintenance of data pipelines that power AI/ML models within the ASM product

Helping build and maintain cloud‑native data platforms that integrate data from various internal and external sources

Designing systems with scalability in mind to support growing data volumes and evolving ML workloads

Optimizing data pipelines for reliability, scalability, and cost efficiency

Assisting in setting up and maintaining CI/CD pipelines for data and ML workloads, with guidance from MLOps and Dev Ops teams

Collaborating closely with Data Scientists, MLOps Engineers, Software Engineers, and Product Owners to understand data needs and deliver solutions

Participating in knowledge sharing and contributing to continuous improvement by applying data engineering best practices

What experience do I need:

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/No

SQL 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.

Benefits:

25 days' holiday + all public holidays

Additional day off for your birthday

Commuting allowance

Pension Scheme

Life & Disability insurance

Employee Assistance Program

Bicycle Leasing Scheme

#J-18808-Ljbffr