Position: Lead Infrastructure Developer (DevOps)
Company: Zoolatech
Experience required: 5y
English level: intermediate

Responsibilities
Seek out ThingsThatShouldGetDone™ and take pride in doing them well and quickly
Improve the velocity and self-sufficiency of the development teams. For our developers
We give them tools to create their infrastructure,
We provide documents and expertise on how to do that well, and
As a last resort, we do DevOps-y things for them
Be a dedicated subject-matter-expert to development teams—you are the liaison between software development and infrastructure
Design, build and extend our automated deployment pipelines supporting continuous integration and delivery (CI/CD) for multiple teams
Document and champion DevOps processes and tools across the organization
Share team on-call responsibility for our always-on 24/7, high-availability SaaS platform with a focus on performance and scalability
Go hands-on to troubleshoot issues and outages, and craft new solutions

Skills Required
A love for creating innovative solutions no one else has solved before
Expertise and experience in Computer Science or related Information Technology field—your degree is great but far less important than what you know and who you are
In-depth working knowledge (e.g. 5 years) of DevOps practices
Solid coding/scripting skill (e.g. 5 years) — especially Python for automation tools
Foundational (e.g. 3-4 years) AWS, Linux, Windows 2012+, VMWare, and network skills
Demonstrated ability to learn, implement and evangelize new technologies
Strong (e.g. 2 years) experience automating cloud and on-premises Infrastructure-as-Code (Terraform, Chef, Puppet, Ansible) and CI/CD pipelines (GitLab, AWS Code Commit, Build, Deploy, and Pipeline)
Understanding of Kubernetes/EKS
Huge Plus: telecom stack (Freeswitch, NTEX, WebRTC, or telecom-as-a-service like Twilio)
Knowledge of monitoring and logging tools (AppDynamics/SignalFX, Grafana, Prometheus)
Hands-on with distributed data stores like Cassandra, Mongo, Redis, ElasticSearch, DynamoDB, DocDB, Airflow, and/or big data like AWS EMR, Kafka, Spark, Kinesis, Hadoop