Our stack I created/managed on was:

• GoLang/Python/MAKE

• Terraform

• Packer

• AWS

• Jenkins

• Kubernetes

• razee.io

• Manage infrastructure in AWS and GCP cloud providers, as well as on prem

• Automated spin up/tear down of AWS and GCP instances using Terraform

• Heavy use of Ansible playbooks to provision instances spun up by via Terraform

• Migrated Jenkins from on prem with static slaves to EC2 running on docker and dynamic slaves

• Built continuous integration pipeline to test against multiple flavors of HDFS using Docker

• Use bash/Python for systems automation

• Worked on build out of new colocation

• General troubleshooting of “production” issues.

• Collaborated with engineering to provide them what they needed.

• Use SALT to orchestrate all of our machines to make bulk changes.

• Design and support multiple multitenant Cloudera Hadoop clusters.

• Collect metrics using Graphite/Grafana.

• Monitor systems using Nagios and Pagerduty.

• Write a lot of bash or python scripts to do special checks or gather special metrics for systems.

• Support several products running on AWS.

• General troubleshooting of production issues.

• Collaborate heavily with engineering teams to set up systems that can support their applications

I worked on a team that supported the Hortonworks Data Platform (Hadoop) for hundreds of customers globally. Daily I would troubleshoot very complex customer issues where they were running the Hortonworks Data Platform (Hadoop). Due to working with customers running Hadoop, I had to handle a lot of high stress situations with critical customer production issues daily. Not only did I have to resolve technical issues but also handle very sensitive customer situations, I focused on specilizing in the following Hadoop components: HDFS, YARN, MapReduce, Oozie, Hive, Pig, Sqoop and Falcon. I also used JIRA and SalesForce daily to get tasks done.