Himalayas · Partner listingSite Reliability Engineer, Big Data (Remote, International)
PulsePoint
⌖ United KingdomSalary not providedRemoteNot specified · Full-time
Source: Himalayas ↗
Location & working arrangementWorking arrangement is supplied by the provider. Check the original advert for attendance and travel requirements.
Provider location / applicant eligibility: United Kingdom
About the role
WebMD and its affiliates is an Equal Opportunity/Affirmative Action employer and does not discriminate on the basis of race, ancestry, color, religion, sex, gender, age, marital status, sexual orientation, gender identity, national origin, medical condition, disability, veterans status, or any other basis protected by law.
Build streaming and storage systems at PulsePoint
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.
What you'll work on
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.
Technology
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.
Who we're looking for
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
Why this role
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.
You can work fully remotely and get the opportunity to work on large-scale infrastructure and distributed systems challenges.
Hiring process
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.
Originally posted on Himalayas
Skills mentioned in the listing
SQLKubernetesIncident responseTerraformAnsibleSQL ServerBackup and recovery
Recognised skills are extracted from the supplied description using canonical names and aliases. They are mentions, not verified essential requirements. Check the source advert for the employer’s full requirements and location restrictions.
Why these skills appear
SQL · mentioned
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. Tec
Kubernetes · mentioned
the role. Technical discussion (~60m) Deep dive into systems engineering, Kubernetes and operational experience. Architecture discussion (~60m) Explore platform design, distributed systems and technical decisi
Incident response · mentioned
own the lifecycle from architecture through deployment to capacity planning and incident response. What you'll work on Kafka architecture, topic design, governance, partition strategy, throughput and latency optimizati
Terraform · mentioned
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-meta
Ansible · mentioned
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 a
SQL Server · mentioned
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. Tec
Backup and recovery · mentioned
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. Technology A