Requirements
4+ years of relevant experience in running distributed systems at scale in production.
Expertise in one of the programming language: Java, Python or Go.
Proficient in writing bash scripts
Good understanding of SQL and NoSQL systems
Good understanding of systems programming (network stack, file system, OS services)
Understanding of network elements such as firewalls, load balancers, DNS, NAT, TLS/SSL, VLANs etc
Skilled in identifying performance bottlenecks, identifying anomalous system behavior, and determining the root cause of incidents.
Knowledge of JVM concepts like garbage collection, heap, stack, profiling, class loading, etc.
Knowledge of best practices related to security, performance, high-availability, and disaster recovery.
Demonstrate a proven record of handling production issues, planning escalation procedures, conducting post-mortems, impact analysis, risk assessments and other related procedures.
Able to drive results and set priorities independently
BS/MS degree in Computer Science, Applied Math or related field


Bonus Points if you have:
Experience with managing large scale deployments of search engines like Elasticsearch
Experience with managing large scale deployments of message-oriented middleware such as Kafka
Experience with managing large scale deployments of RDBMS systems such as oracle
Experience with managing large scale deployments of NoSQL databases such as Cassandra
Experience with managing large scale deployments of In-memory caching using Redis, Memcached, etc.
Experience with container and orchestration technologies such as Docker, Kubernetes etc
Experience with monitoring tools such as Graphite, Grafana and Prometheus
Experience with Hashicorp technologies such as Consul, Vault, Terraform and Vagrant
Experience with configuration management tools such as Chef, Puppet or Ansible
In-depth experience with continuous integration and continuous deployment pipelines
Exposure to Maven, Ant or Gradle for builds