Job Description :
Job Description:
Staff System Engineer, works on complex projects, and creates innovate solutions to improve R&D productivity. This highly technical individual must possess strong knowledge of core infrastructure components including HPC compute, server farm, networking, storage, backups and the associated management, monitoring, and automation of these areas. R&D Solutions Staff System Engineer will partner with Solutions and Enterprise architects in cross-functional teams taking conceptual architectures, repeatable patterns, and decision frameworks to an implementable solution design.
Duties & Skills:
· Works on server farms design/redesign, solution architecture design, infrastructure design and planning, system upgrades and migrations, acceptance testing, and maintenance strategy development according to established roadmaps.
· Possesses an in-depth understanding of relevant technology trends, technical tools and platforms, and emerging/evolving software and services related to software development, including compute farms, job submission/management technologies, cloud, hybrid-cloud, and associated monitoring, reporting, and management tools.
· Manages daily operations of compute clusters across Cadence Locations.
Specific Ongoing Duties:
· Provide system/farm expertises in timely resolution of R&D user issues in server farms.
· Work closely with R&D user community to improve user productivity and farm resource utilization.
· Regular knowledge transfers to direct team and cross-functional peers in IT.
· Work with global teams in different time zones to achieve common goals.
· Participate in M&A activities.
Education & Experience:
· Four year degree (Computer Science, Information Systems or relational functional field) and/or equivalent combination of education or work experience. Advanced degree preferred
· Eight or more years of professional experience in the field of Information Technology and Enterprise
· Hand-on experience and in-depth knowledge with trouble shooting various user job issues in a compute farm.
· Experience with optimizing linux system configurtions for better performance. Knowledge of cpu/memory affinity and cgroups, and how they can be used for better process control.
Architecture:
· Expertise in distributed computing in a server farm environment.
· Experience with cloud computing architecture in a hybrid model is a significant benefit.
· Operating system platform technology knowledge from major vendors and open source solutions, including Linux, LSF, Openlava, SGE, ElasticSearch, Cacti, Nagios, Zabbix, etc.