Senior Storage Engineer: Cloud & On-Prem Automation

Balyasny Asset Management L.P.

New York (NY)

Sur place

USD 150 000 - 190 000

Plein temps

Il y a 2 jours
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Résumé du poste

Balyasny Asset Management L.P. is seeking an experienced Storage Engineer in New York to manage large-scale storage across on-prem and cloud.

You will collaborate with Portfolio Managers and stakeholders to understand data needs and enable them to use our storage platforms effectively. You will automate provisioning, optimize data lifecycle, monitor performance and capacity, and develop resilient DR procedures.

Qualifications

  • 6+ years of hands-on experience with large-scale storage environments.
  • Experience with software low latency environments.
  • Strong understanding of storage protocols across operating systems.
  • Comfortable writing Python.
  • Experience with disaster recovery and business continuity planning.

Responsabilités

  • Handle block, file and object storage platforms on-prem and in the public cloud.
  • Advance automation around storage provisioning and data lifecycle.
  • Create robust monitors around performance, capacity and efficiency.
  • Define acceptable use patterns for each storage system, guide teams towards these patterns and hold teams accountable to misuse.
  • Engineer tools and automation for routine disaster recovery tests across all storage platforms.
  • Partner with application developers across the firm and enable their success.
  • Participate in on-call rotation and maintenance.

Connaissances

Storage engineering
Python
Automation
Monitoring
On-call experience

Outils

AWS EBS
S3
FSxN
Pure Storage
NFS
CIFS
iSCSI
Linux
Windows Server
RDMA over Ethernet

Description du poste

Balyasny Asset Management L.P. is seeking an experienced Storage Engineer in New York to manage large-scale storage across on-prem and cloud.

You will collaborate with Portfolio Managers and stakeholders to understand data needs and enable them to use our storage platforms effectively. You will automate provisioning, optimize data lifecycle, monitor performance and capacity, and develop resilient DR procedures.

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