Sizing Architects deliver accurate hardware estimates for Software Sales Opportunities (SSOs), collaborating with account teams, R&D, and platform partners.

Sizing Team

• Ability to lead or support multiple, occasionally complex, projects using time management, accountability, and communication for successful project completion
• Provide precise hardware sizing recommendations tailored to business requirements and solution architecture, supporting global sales initiatives.
• Oversee the sizing request queue to ensure high-quality, consistent output aligned with the latest methodologies.
• Collaborate closely with internal SAS teams, R&D experts, and field consultants to ensure the accuracy and relevance of benchmarks and sizings.
• Support sales and pre-sales efforts by offering expert guidance on sizing and performance through calls, chats, and emails.
• Contribute to the strategic development of the sizing program through planning, stakeholder engagement, and proactive knowledge sharing.
• Promote a collaborative team culture by removing obstacles, sharing progress updates, and supporting peer success.

Technical Skills

• System administration (Linux, Windows Server), Storage systems (SAN, NAS, NFS, Storage protocols (FCoE, Fibre Channel, CIFS, JBOD)

• Working knowledge of CPUs (physical/virtual), chipsets, NUMA, cache, pipelining, and CPU affinity
• Hands-on experience with leading cloud platforms—Azure, AWS, and Google Cloud, including instance types, networking, VM scale sets (VMSS), placement groups, and storage solutions.

• Multi-Tier Architecture: Experience supporting and maintaining multi-tier application environments.
• Hardware Platforms: Experienced with Dell and HPE systems, focusing on performance and storage.

• Experience with Kubernetes on cloud platforms, Azure AKS preferred, followed by AWS, GCP, OpenShift, and open source)

• Performance Troubleshooting: Skilled in diagnosing performance issues across hardware, OS, applications, and network layers.

• Proficient in analyzing the interplay between hardware architecture and workload demands to optimize capacity planning and software efficiency.
• Understanding of storage subsystems (RAID, SAN, NFS, ANF), I/O throughput, and latency
• Understanding of networking technologies and limitations (bandwidth, latency, packet loss)