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3 дня назад

Site Reliability Engineer (Big Data)

Формат работы
remote (Global)
Тип работы
fulltime
Грейд
senior
Английский
b2
Страна
UK
Вакансия из списка Hirify.GlobalВакансия из Hirify RU Global, списка компаний с восточно-европейскими корнями
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Описание вакансии

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TL;DR

Site Reliability Engineer (Big Data): Building and optimizing streaming and storage systems with an accent on Kafka architecture and Ceph operations. Focus on automating operational workflows, managing petabyte-scale distributed systems, and ensuring high availability across hybrid infrastructure.

Location: Remote (International). Willingness to work 9am-6pm ET U.S. hours is required.

Company

hirify.global is a high-scale data platform processing billions of events daily using Kafka, Hadoop, and Ceph.

What you will do

  • Manage Kafka architecture, including topic design, partition strategy, throughput, and latency optimization.
  • Oversee Ceph operations, pool design, placement optimization, and capacity planning.
  • Develop operational automation to reduce manual work and accelerate incident response.
  • Maintain SQL Server backup and recovery pipelines and provide basic cluster support.
  • Build self-service tooling and observability frameworks for the data team.

Requirements

  • 5+ years of experience operating large-scale distributed systems in production.
  • Deep expertise in Kafka, Ceph, or similar distributed infrastructure.
  • Proven ability to design for scale and reliability at petabyte scale.
  • Experience mentoring engineers and making critical technical decisions.
  • Must be willing to work 9am-6pm ET U.S. hours.

Nice to have

  • Experience with multi-region replication and disaster recovery.
  • Cost optimization expertise at infrastructure scale.
  • Experience with hybrid on-prem/cloud operations.

Culture & Benefits

  • Fully remote work arrangement.
  • Opportunity to define platform architecture and influence engineering standards.
  • High-impact role as a key technical contributor shaping the future of the platform.
  • Exposure to large-scale distributed systems challenges.

Hiring process

  • Introductory conversation to discuss background and the role.
  • Technical discussion focused on systems engineering and Kubernetes.
  • Architecture discussion exploring platform design and technical decision-making.
  • Leadership conversation regarding team strategy and long-term direction.

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