Platform Engineer

Datacenter Engineering Group Position

We would prefer someone who is semi-local to Madison, Wisconsin or willing to commute up to 10 days per month. We are open to remote engineers as well.

Position will be a member of the Datacenter Engineering Group within Enterprise IT with an initial focus on private cloud service delivery or the delivery of infrastructure solutions running across both public (AWS, GCP and Azure) and private cloud environments. In addition the uniqueness of this roll I am looking for will have a candidate that will be responsible for developing data pipeline architectures (including infrastructure) which includes extracting, aggregating, and analyzing infrastructure performance data alongside business data to forecast infrastructure capacity/trending/risk needs.

This role requires a blend of data pipeline/engineer and engineering skills to create simulations and predictive models.

In addition to the technical competencies outlined in the job description, the ideal candidate will have experience with at least a subset of the following:

• This roll will require a blend of engineering skills with a strong background in data analysis, forecasting and data pipeline infrastructure
• automation of infrastructure delivery with configuration orchestration and management solutions (e.g. Ansible/AAP and Terraform)
• understanding of coding practices, source code control (Gitlab) and developing in a preferred scripting language (e.g. Python, UNIX Shell Scripting)
• strong experience with Linux and Windows systems engineering principles
• strong understanding of application resiliency and data resiliency across multiple platforms.
• Strong hands on experience in data observability tools such as Datadog
• experience in data pipeline engineering and architecture which can focus on extracting, aggregating and analyzing infrastructure performance data alongside business data to forecast infrastructure capacity needs.
• This engineer should be able to take a data analysis problem and produce recommendations, architecture, and create a pipeline to produce a result to the problem.
• Collaboration and Communication:
• Work closely with cross-functional teams to understand business requirements and drivers.
• Communicate findings and recommendations to stakeholders through reports and presentations.
• Create and maintain comprehensive documentation for data processes and models.
• Ensure compliance with company policies, industry standards, and regulatory requirements.