PulsePoint
AdTech & Programmatic Advertising
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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
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.
Introductory conversation (~60m)
Learn about your background and discuss the role.
Technical discussion (~60m)
Deep dive into systems engineering, Kubernetes and operational experience.
Architecture discussion (~60m)
Explore platform design, distributed systems and technical decision-making.
Leadership conversation (~30m)
Meet engineering leadership and discuss team, strategy and long-term direction.
After you apply, unlock the direct contact details of the people who actually make the call. A quick follow-up makes you 5x more likely to land an interview.
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