Cloud Storage Engineer

SAIC•New Orleans, LA

60d

About The Position

SAIC is seeking a highly skilled and experienced Data & Storage Integration Engineer with a strong background in software integration, data science, and enterprise storage systems. The ideal candidate will bring advanced expertise in scripting, data analytics, storage technologies, and enterprise systems to support complex integration, performance, and analytics objectives across a dynamic IT environment.

Requirements

Bachelor’s Degree with a minimum of 14 years of relevant experience
Familiarity with NetApp tools including OnCommand, Active IQ, System Manager
CompTIA Storage+ or equivalent certifications
Analytical thinking and problem-solving mindset
Excellent written and verbal communication
Ability to work independently and collaboratively in a 24/7 support environment
Experience in documenting technical solutions and managing cross-functional projects
MUST BE A US CITIZEN WITH THE ABILITY TO OBTAIN A SECRET SECURITY CLEARANCE

Nice To Haves

Experience with AWS cloud storage services (e.g., S3, EBS, FSx, Storage Gateway)
NetApp Certified Data Administrator (NCDA)
NetApp Certified Implementation Engineer (NCIE)
Integrate with cloud platforms (e.g. AWS, NetApp Cloud Manager, FSxN)
Work with virtualization technologies (e.g., VMware, Xen, KVM)

Responsibilities

Design, deploy, configure, and maintain NetApp storage systems (e.g., FAS, AFF, E-Series, 8200, 8300, A300)
Manage storage protocols (NFS, CIFS/SMB, iSCSI, FC) and ONTAP operating systems
Monitor performance, implement provisioning, and configure storage virtual machines (SVMs)
Develop statistical and operations research models to support business and technical objectives
Design and execute data mining, graph algorithms, or analytics pipelines
Implement SnapMirror, SnapVault, and SnapRestore technologies
Support data backup, disaster recovery planning, and storage consolidation
Analyze storage performance metrics and optimize configurations
Implement quality of service (QoS) policies
Troubleshoot storage-related performance issues
Capacity planning and forecasting
Design and implement APIs and ETL pipelines for large-scale data movement
Collaborate with network, server, application, and database teams to meet data delivery requirements
Apply scripting languages (Python, R) and tools (Jupyter, Pandas, NumPy, Requests) in support of data science or advanced analytics
Proficiency with operating systems (Linux, Windows Server) and enterprise networking