About Hadrian
At Hadrian, that's exactly what we're building: the future of offensive cybersecurity, powered by autonomous AI agents that think like hackers. Founded in Amsterdam in 2021, we're on a mission to change the way organisations defend themselves by helping them find and fix security weaknesses before attackers can exploit them.
Responsibilities
•Own and operate Hadrian's end-to-end data platform, ensuring reliability, scalability, and performance across the entire data stack.
•Lead strategic data architecture initiatives and help shape the future of Hadrian's AI and MLOps data foundation.
•Maintain, troubleshoot, and optimize data integrations, connectors, and pipelines built on Airbyte, dbt, and BigQuery.
•Build and evolve data models, transformations, and semantic layers that power analytics, business operations, and AI initiatives.
•Drive operational excellence by improving platform reliability, monitoring, and incident response processes.
•Partner with stakeholders across Engineering, AI, Security, and Business teams to deliver trusted and actionable data products.
•Evaluate and implement modern data platform capabilities, including orchestration, streaming architectures, and Lakehouse technologies.
•Build tooling and automation that improves developer and analyst productivity.
Requirements
•Have 5+ years of professional Data Engineering experience, ideally in a fast-paced startup or scale-up environment.
•Have deep hands-on experience with Airbyte and understand data replication, connector management, and troubleshooting at scale.
•Are highly proficient with dbt, SQL, and Python, and have extensive experience building and maintaining transformation pipelines.
•Have experience working with GCP and AWS environments, including managing data storage (S3 / Cloud Storage) and identity management (IAM).
•Can operate independently and take full ownership of a business-critical data platform without requiring significant day-to-day guidance.
•Apply strong software engineering principles and best practices to data infrastructure.
•Balance operational excellence with long-term architectural thinking.
•Use AI pragmatically to accelerate workflows while maintaining high standards of quality and reliability.
•Communicate effectively with both technical and non-technical stakeholders.
•Share our values and work in accordance with them.
Nice to have
•Experience with Kafka, Strimzi, Redis, or other streaming, caching, and in-memory data platforms.
•Experience utilizing Redis or dedicated feature stores to support real-time MLOps and AI/LLM workloads.
•Familiarity with Lakehouse architectures and Semantic Layer implementations.
•Experience with Kubernetes, Helm, Terraform/OpenTofu, or cloud infrastructure automation.
•Experience with Scaleway or multi-cloud environments.
•Contributions to open-source data, analytics, or MLOps projects.
•Experience deploying or optimizing infrastructure supporting LLM workloads and AI applications.
Conditions / Benefits
•Unlimited paid holiday
•Stock options package
•Mobile phone stipend
•Work-from-home budget
•Business travel card
•Swapfiets
•Referral bonuses
