Data Reliability Engineer- Remote OK

Splunk

Boulder Colorado

United States

Information Technology
(No Timezone Provided)

Data Reliability Engineer - Remote OK Join us as we pursue our disruptive vision to make machine data accessible, usable and valuable to everyone. We are a company filled with people who are passionate about our product and seek to deliver the best experience for our customers. At Splunk, we're committed to our work, customers, having fun and most significantly to each other's success. Learn more about Splunk careers and how you can become a part of our journey! Team works US Eastern Time Zone hours. Role: As part of Splunk's Cloud-First mission, the Data Reliability team is accountable for data governance, including the overall quality, reliability, and accessibility of data collected in our cloud production environments. We are data engineers, site reliability engineers, and Splunk specialists who engage with product and infrastructure teams at every level, from directly embedding on their teams to tagging in for the gnarliest of data challenges! Our goal is to make high quality, compliant, predictable data that is easy to access and used to make meaningful actions that improve our customers' experiences. You will: Work across the organization to deliver quality data that can be used by teams ranging from incident response, SRE teams, service owners, and sales. Lead teams of tight-knit engineers who are building a state-of-the-art, cloud-based environment for massive-scale data processing. Mentor and help new engineers to achieve more than they thought possible. You enjoy making other teams successful and are fulfilled through the success of others. Preferred Skills: 5+ years of related experience with a technical Bachelor's degree; or equivalent practical experience. Strong software engineering skills in Python and/or Golang. Experience with collecting metrics from multi-cluster Kubernetes environments and strong understanding of multi-tenancy and security implications. Experience with large scale distributed cloud service development, infrastructure, traffic management and architecture (AWS or GCP preferred). Understanding of observability, logging, and monitoring platforms (Splunk, ELK, New Relic, AppDynamics, Dynatrace, etc.). Dedication to standard methodologies related to security, performance, and disaster recovery. Nice to have: An expert on Splunk data and its various use cases. Good understanding of Security and IT Operations use cases and how customers expect to interact with log data. Develop and maintain methods to retrieve, condition, validate, synthesize, and manipulate data. Experience manipulating and interpreting large and diverse datasets. Experience developing and operating accurate, secure, stable data pipelines using modern cloud technologies. Background in data engineering or data science. We value diversity at our company. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or any other applicable legally protected characteristics in the location in which the candidate is applying. For job positions in San Francisco, CA, and other locations where required, we will consider for employment qualified applicants with arrest and conviction records.

Data Reliability Engineer- Remote OK

Splunk

Boulder Colorado

United States

Information Technology

(No Timezone Provided)

Data Reliability Engineer - Remote OK Join us as we pursue our disruptive vision to make machine data accessible, usable and valuable to everyone. We are a company filled with people who are passionate about our product and seek to deliver the best experience for our customers. At Splunk, we're committed to our work, customers, having fun and most significantly to each other's success. Learn more about Splunk careers and how you can become a part of our journey! Team works US Eastern Time Zone hours. Role: As part of Splunk's Cloud-First mission, the Data Reliability team is accountable for data governance, including the overall quality, reliability, and accessibility of data collected in our cloud production environments. We are data engineers, site reliability engineers, and Splunk specialists who engage with product and infrastructure teams at every level, from directly embedding on their teams to tagging in for the gnarliest of data challenges! Our goal is to make high quality, compliant, predictable data that is easy to access and used to make meaningful actions that improve our customers' experiences. You will: Work across the organization to deliver quality data that can be used by teams ranging from incident response, SRE teams, service owners, and sales. Lead teams of tight-knit engineers who are building a state-of-the-art, cloud-based environment for massive-scale data processing. Mentor and help new engineers to achieve more than they thought possible. You enjoy making other teams successful and are fulfilled through the success of others. Preferred Skills: 5+ years of related experience with a technical Bachelor's degree; or equivalent practical experience. Strong software engineering skills in Python and/or Golang. Experience with collecting metrics from multi-cluster Kubernetes environments and strong understanding of multi-tenancy and security implications. Experience with large scale distributed cloud service development, infrastructure, traffic management and architecture (AWS or GCP preferred). Understanding of observability, logging, and monitoring platforms (Splunk, ELK, New Relic, AppDynamics, Dynatrace, etc.). Dedication to standard methodologies related to security, performance, and disaster recovery. Nice to have: An expert on Splunk data and its various use cases. Good understanding of Security and IT Operations use cases and how customers expect to interact with log data. Develop and maintain methods to retrieve, condition, validate, synthesize, and manipulate data. Experience manipulating and interpreting large and diverse datasets. Experience developing and operating accurate, secure, stable data pipelines using modern cloud technologies. Background in data engineering or data science. We value diversity at our company. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or any other applicable legally protected characteristics in the location in which the candidate is applying. For job positions in San Francisco, CA, and other locations where required, we will consider for employment qualified applicants with arrest and conviction records.