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PulsePoint processes billions of events daily through Kafka, Hadoop HDFS and Ceph. Our Data Platform team maintains these systems across hybrid infrastructure: bare-metal on-prem, cloud, and the integration between them. You own the lifecycle from architecture through deployment to capacity planning and incident response.

• Kafka architecture, topic design, governance, partition strategy, throughput and latency optimization.

• Ceph operations, pool design, placement optimization, capacity planning.

• Operational automation, reduce manual work, faster incident response, preventive systems.

• SQL Server backup and recovery pipelines, basic cluster support.

• Data team tooling with self-service capabilities and observability.

• Apache Kafka for messaging layer

• Hadoop and Ceph as distributed storage layer

• SQL Server backup and recovery

• Terraform, Ansible, Puppet, ArgoCD for operational automation

• Prometheus, Grafana, Icinga and PagerDuty as observability layer

• Bare-metal servers and hybrid cloud/on-prem infrastructure

What matters: understand distributed systems, failure recovery, and operational patterns at scale. Apache Kafka and Ceph expertise is most valuable.

You've operated data infrastructure at petabyte scale or billions of events/day. You understand replication failures, consistency tradeoffs, and cost-optimization of large systems. You automate before troubleshooting. You take ownership across system layers, not just one component. You simplify complex systems.

Requirements:

• 5+ years operating distributed systems at scale in production

• Deep expertise in Kafka, Ceph, or similar distributed infrastructure

• Proven ability to design for scale and reliability

• Experience mentoring engineers and making technical decisions

• Willingness to work 9am-6pm ET U.S. hours

Nice-to-haves:

• Multi-region replication and disaster recovery

• Cost optimization at infrastructure scale

• Hybrid on-prem/cloud operations

This is not a ticket-driven operational role.

You'll help define platform architecture, influence engineering standards and work on infrastructure that supports multiple engineering organizations.

The engineer joining this role is expected to become a key technical contributor shaping the future of the platform.

We try to keep the process focused and practical.

1. Introductory conversation (~60m)
   Learn about your background and discuss the role.

2. Technical discussion (~60m)
   Deep dive into systems engineering, Kubernetes and operational experience.

3. Architecture discussion (~60m)
   Explore platform design, distributed systems and technical decision-making.

4. Leadership conversation (~30m)
   Meet engineering leadership and discuss team, strategy and long-term direction.