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Storage Performance Engineer Jobs in Round Rock, TX

Hirekeyz Inc

SAP Performance Engineer

Austin, TX · On-site

Title: SAP Performance Engineer Location: Austin, TX Job Type: Full Time For this role, we are ... AWS storage services. * Skilled in BTP technologies like Smart Data Integration (SDI) & Hana ...

3M HEALTHCARE

Systems Performance Engineer

Austin, TX · On-site

$150 - $200/hr

Micron Technology is a world leader in innovating memory and storage solutions that accelerate the ... The engineer works with senior engineers and researchers on AI training and inference systems ...

Nvidia

Senior HPC Storage Engineer

Austin, TX · On-site

Experience analyzing and tuning storage performance for a variety of workloads. Proficient in ... Hardware & Storage Engineering: Deep familiarity with storage hardware (HDDs, SSDs, NVMe ...

BitDeer

AI Storage Solutions Expert

Austin, TX · On-site +1

$180K - $320K/yr

In this role you deploy and operate the high-performance storage layer for AI training and inference across NeoCloud's US DCs, and you feed the AIOps substrate with the signals it needs to catch ...

Nvidia

Senior HPC Storage Engineer

Austin, TX · On-site

Experience analyzing and tuning storage performance for a variety of workloads. * Proficient in ... Hardware & Storage Engineering: Deep familiarity with storage hardware (HDDs, SSDs, NVMe ...

Nvidia

Senior Performance Engineer - DGX Cloud

Austin, TX · On-site

$103K - $142K/yr

We help AI researchers and platform teams understand end-to-end behavior across GPUs, networking, storage, and software stacks. We are seeking a Senior Performance Engineer to characterize workloads ...

Nvidia

Senior Performance Engineer - DGX Cloud

Austin, TX · On-site

$103K - $142K/yr

We help AI researchers and platform teams understand end-to-end behavior across GPUs, networking, storage, and software stacks. We are seeking a Senior Performance Engineer to characterize workloads ...

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Storage Performance Engineer information

See Round Rock, TX salary details

$10

$56

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How much do storage performance engineer jobs pay per hour?

As of Sep 9, 2026, the average hourly pay for storage performance engineer in Round Rock, TX is $56.05, according to ZipRecruiter salary data. Most workers in this role earn between $45.96 and $63.46 per hour, depending on experience, location, and employer.

What is a storage performance engineer?

Storage Performance Engineers are IT professionals who specialize in analyzing, optimizing, and troubleshooting the performance of storage systems, such as SAN, NAS, and cloud storage. They work to ensure data is stored, retrieved, and managed efficiently to support the needs of applications and users. Their responsibilities include monitoring storage metrics, identifying bottlenecks, tuning system parameters, and collaborating with other IT teams to maintain optimal storage performance. These engineers often work with both hardware and software components and may also help plan for future storage needs.

What are some common challenges a storage performance engineer faces when optimizing storage systems in large-scale environments?

A Storage Performance Engineer often encounters challenges such as balancing performance with cost-efficiency, managing latency and throughput bottlenecks, and ensuring compatibility across diverse hardware and software platforms. In large-scale environments, diagnosing performance issues can be complex due to the sheer volume of data and the variety of workloads. Collaboration with infrastructure, application, and DevOps teams is essential to identify root causes and deploy effective solutions, requiring both technical expertise and strong communication skills.

What are the key skills and qualifications needed to thrive as a storage performance engineer, and why are they important?

To thrive as a Storage Performance Engineer, you need in-depth knowledge of storage architectures, performance tuning, and data management, often supported by a degree in computer science or a related field. Familiarity with storage systems (such as SAN, NAS), performance monitoring tools, and certifications like SNIA or vendor-specific credentials are typically important. Analytical thinking, problem-solving, and strong communication skills help distinguish top performers in this role. These skills are essential to ensure optimal storage performance, minimize downtime, and support business-critical data operations.

What is the difference between Storage Performance Engineer vs Storage Systems Analyst?

AspectStorage Performance EngineerStorage Systems Analyst
CredentialsTypically requires a degree in Computer Science or related field, certifications like SNIA SNLP or vendor-specific certificationsUsually holds a degree in IT or Computer Science, with certifications such as CompTIA Storage+ or vendor-specific certifications
Work EnvironmentHands-on with storage hardware, performance testing, and optimization in data centers or enterprise environmentsAnalyzes storage system performance, reports, and recommends improvements, often in office or remote settings
Industry UsageCommon in data centers, cloud providers, and enterprise IT teamsFound in IT departments, consulting firms, and enterprise organizations

While both roles focus on storage systems, Storage Performance Engineers specialize in optimizing storage performance through testing and hardware tuning, whereas Storage Systems Analysts focus on analyzing and reporting storage performance data to inform improvements.

Infographic showing various Storage Performance Engineer job openings in Round Rock, TX as of August 2026, with employment types broken down into 84% Full Time, 14% Part Time, and 2% Contract. Highlights an 75% Physical, 2% Hybrid, and 23% Remote job distribution, with an average salary of $116,584 per year, or $56 per hour.

MongoDB Performance Engineer

Austin, TX • On-site

Volto USA
See more jobs at Volto USAexternal

Contractor

Posted 16 days ago

Job description

Job Title: Sr MongoDB Performance Engineer
Role Descriptions:
Must Have Skills:
1. Expert in MongoDB
2. Strong experience in Performance tuning
3. Fluent in the aggregation framework, indexing strategy, and read/write/read-concern semantics.
4. Strong explain-plan and profiler-driven query optimization
5. WiredTiger internals: cache, eviction, checkpoints, journal, compression, document-level concurrency.
6. Replication and sharding operations at scale, including shard-key design trade-offs.
7. Scripting for automation – Python
8. Strong experience with tuning of specific clusters, queries, indexes and schemas
9. Good experience designing sharding strategy and shard keys; plans resharding and zone strategy
10. Strong experience operating and monitoring existing sharded clusters; runs balancer, fixes hot chunks
Nice To Have Skills:
1. MongoDB certification
2. Kubernetes operator experience for stateful MongoDB; Infrastructure-as-Code (Terraform/Ansible).
Technical/Functional Skills:
MongoDB Performance Engineer to own the throughput, latency, scalability and operational reliability of MongoDB landscape. This is a hands-on database engineering role — not an application-developer role.
The engineer is accountable for making MongoDB fast, predictable and cost-efficient at scale.
Performance engineering (Primary)
• Profile and optimize slow queries and aggregation pipelines using explain plans, the database profiler, and log analysis.
• Design, review and rationalize indexes (compound, partial, wildcard, Time To Live (TTL), text, geospatial) applying the Equality, Sort, Range (ESR) rule; eliminate unused and redundant indexes that inflate write cost and cache pressure.
• Tune the WiredTiger storage engine: internal cache sizing, eviction and checkpoint behavior, compression, and journaling, balanced against filesystem cache.
Operations & reliability
• Operate and scale sharded clusters: balancer management, chunk/range distribution, jumbo-chunk remediation, and (on modern versions) resharding.
• Own backup/restore and Point-In-Time Recovery (PITR) strategy, plus rolling upgrades and patching with zero or minimal downtime.
Infrastructure, OS & platform
• Right-size EC2 instances and EBS volumes (Input/Output Operations Per Second (IOPS) and throughput provisioning); on Kubernetes, own StatefulSet storage class, resource requests/limits, anti-affinity, and cache sizing against container memory limits.
Partner with application teams on data modeling; review schema changes; publish standards, runbooks and capacity guidance.
Skills: Digital : Mongo DB~Performance Engineering