Staff Infrastructure Engineer

Copenhagen, Capital Region
Posted 2 weeks, 5 days ago
Engineering

About the role

Job summary

The Ads Infrastructure team is responsible for building and maintaining the core distributed systems that support a major real-time advertising platform. The focus is on creating resilient, scalable, and cost-efficient systems that facilitate segmentation, optimization, bidding, and analytics at a global scale.

Qualifications

  • Minimum of 7 years of experience in building and operating large-scale distributed systems in production environments.
  • Proficient in backend service and infrastructure development programming.
  • Hands-on experience with Kubernetes and cloud-native systems in GCP, AWS, or Azure.
  • Strong expertise in distributed infrastructure, including traffic management, load balancing, networking, and large-scale data processing.
  • In-depth understanding of networking, observability, and debugging of distributed systems.

Responsibilities

  • Lead the architecture and low-level design of distributed systems to ensure scalability, reliability, and efficiency.
  • Manage and operate infrastructure services alongside engineering teams, including on-call duties and complex issue debugging.
  • Assist engineering teams with onboarding and utilizing platform-managed services.
  • Enhance operational excellence through improved observability, resiliency, and automation.
  • Mentor engineers and elevate technical standards through design and code reviews.
  • Provide strategic advice to leadership regarding platform direction and emerging infrastructure technologies.

Skills

  • Expertise in distributed caching or storage systems for large-scale, low-latency workloads is a plus.
  • Familiarity with Kubernetes CI/CD tools such as ArgoCD.
  • Knowledge of protocols, routing, and service discovery in large-scale environments.
  • Domain knowledge in online advertising and adtech systems is advantageous.

Education

  • Relevant degree or equivalent experience in a related field is preferred.

Tools

  • Experience with Kubernetes, Kafka, Flink, and cloud platforms (GCP, AWS, Azure) is essential.
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