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Data Storage Jobs (NOW HIRING)

AWS Data Storage Analyst

Rahway, NJ · On-site

$40 - $45/hr

Develop and maintain data integration, data movement, and laboratory data pipeline solutions. * Configure and manage SMB/CIFS, NFS, and AWS storage services (S3, EFS, FSx, EBS). * Create and maintain ...

Analyze location, cube, velocity, utilization, and material-characteristic data to support stock positioning and storage optimization. * Coordinate bin-to-bin moves, WMS updates, labeling ...

Knowledge of storage hardware technologies. * Knowledge of SAN fabric technologies. * Certifications: Netapp Certified Data Administrator (NCDA), ONTAP or equivalent. Desired Qualifications * Active ...

Data storage team is lacking resources to complete critical tasks. A storage resource is needed to assist with running operations. * Migrate Enterprise Storage from legacy environments to recently ...

They are seeking an experienced Data Center Storage Engineer to provide technical oversight of hardware and software systems, ensuring system security and managing storage area networks to support ...

Understanding of coverged data/storage networks * Very good Powershell skills * Flash experience is desirable * Pure for Block data * NetApp for CiFS and NFS * SnapMirror for NetApp d) Array based ...

Showing results 21-40

Data Storage information

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$14

$37

$108

How much do data storage jobs pay per hour?

As of Aug 22, 2026, the average hourly pay for data storage in the United States is $37.43, according to ZipRecruiter salary data. Most workers in this role earn between $16.59 and $40.38 per hour, depending on experience, location, and employer.

What is data storage and why is it important?

Data storage refers to the process of saving digital information on various types of storage media, such as hard drives, solid-state drives, cloud platforms, or optical discs. It is essential for businesses and individuals to securely store, manage, and access their data when needed. Effective data storage ensures data protection, supports business continuity, and enables efficient information retrieval for operations and decision-making.

What are the typical challenges faced when managing large-scale data storage systems, and how are they addressed within a team setting?

Professionals in data storage roles often encounter challenges such as ensuring data security, minimizing downtime, and optimizing performance as storage needs grow. Addressing these issues typically involves close collaboration with IT, network, and security teams to implement robust backup solutions, monitor system health, and maintain compliance with data regulations. Regular team meetings and cross-functional projects are common, allowing team members to share best practices and quickly respond to incidents, ensuring the reliability and scalability of storage systems.

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

To thrive as a Data Storage Specialist, you need expertise in data management, storage architectures, and backup/recovery solutions, often supported by a degree in computer science or information technology. Familiarity with storage area networks (SAN), network-attached storage (NAS), cloud storage platforms, and certifications like CompTIA Storage+ or vendor-specific credentials are typically required. Strong problem-solving skills, attention to detail, and effective communication help you manage complex systems and collaborate across IT teams. These skills ensure data integrity, security, and availability, which are critical for organizational operations and disaster recovery.

What is the difference between Data Storage vs Data Analyst?

AspectData StorageData Analyst
Required CredentialsKnowledge of database systems, certifications like CompTIA Storage+Degree in statistics, data science, or related fields; certifications like Microsoft Data Analyst
Work EnvironmentData centers, IT departments, cloud storage facilitiesOffice settings, analytics teams, business departments
Employer & Industry UsageIT companies, cloud providers, data centersBusiness, finance, marketing, and healthcare sectors
Common Search & Comparison IntentUnderstanding storage solutions, infrastructure rolesAnalyzing data, generating insights

Data Storage focuses on managing and maintaining data infrastructure, while Data Analysts interpret data to support decision-making. Both roles are essential in data-driven organizations but serve different functions within the data ecosystem.

More about Data Storage jobs

What cities are hiring for Data Storage jobs?

Cities with the most Data Storage job openings:

What are the most commonly searched types of Data Storage jobs?

The most popular types of Data Storage jobs are:

What states have the most Data Storage jobs?

States with the most job openings for Data Storage jobs include:

Infographic showing various Data Storage job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $77,857 per year, or $37.4 per hour.

Research Data Storage Developer

RiseIT Solutions

Princeton, NJ • On-site

$114K/yr

Full-time

Re-posted 29 days ago


Job description

Title: Research Data Storage Developer (15005)
Location: Princeton, NJ (08540)
Type: Perm Role
Rate: $114K per year
Education: Bachelor's degree
Reporting to the Director of Advanced Data and Storage Management, this 3-year term position will provide critical development work on the configuration of custom integrations, workflow, and data extraction processes to assist with the implementation of TigerData, a data storage and management system that supports the advancement of research at the client. Understanding the needs of faculty researchers and collaborating with developers in the Library, you will develop processes and tools for metadata entry and management, automated metadata harvesting from common file types and other campus systems, and automation workflows for ensuring smooth transitions between storage stages, including movement of data to publication and long-term archive.
This is a 3-year benefits-eligible term position.
Job Duties and Responsibilities
  • Build, test, debug, and document software designed to support research data management, including discovery, metadata extraction from common file types and other campus systems, and data movement workflows
  • Develop interfaces for the TigerData presentation layer using API
  • Integrate with data sources such as TigerData, ORCID, Globus, cloud storage, and existing data repositories.
  • Analyze, transform, migrate, and process data and metadata
  • Build tools and workflows to validate research data submissions
  • Automate and streamline manual or inefficient tasks
  • Help plan and estimate work on software projects
  • Embedded with a team of PUL developers working in an agile environment
  • Maintain a strong partnership with the PUL software development group to enhance collaboration in the implementation of TigerData
Qualifications
Essential Qualifications:
  • Minimum of 3-5 years’ experience as a developer working in an environment that includes complex software systems, object-oriented programming, web-based applications and services, and distributed architecture
  • Demonstrated experience with an object oriented language, preferably Ruby or Java
  • Experience building complex web forms that drive workflows and meet contemporary usability guidelines using modern HTML, CSS, and Javascript frameworks
  • Demonstrated experience with test-driven development, preferably using RSpec or JUnit
  • Ability to work in a Linux-based environment
  • Willingness to learn new technologies and data/metadata formats
  • Experience with Agile software development practices
  • Strong oral and written communication skills
  • Education: A bachelor’s degree or equivalent experience.
Preferred Qualifications:
  • Experience with relevant cultural heritage metadata formats (such as MARC, MODS, and Dublin Core); ideally with archival and/or geospatial metadata formats
  • Experience with Python or R
  • Experience with research data management and institutional repositories
  • Experience with data harvesting APIs such as OAI-PMH or ResourceSync
  • Familiarity with best practices for data modeling and data management
  • Experience working on and contributing to open source software projects
  • Proficiency with common tools for source code version control, collaboration, and deployment; such as Git, GitHub, Capistrano and Ansible
  • Experience with DevOps and deployment automation
Advanced degree in Library Science, Computer Science, Geographic Information Systems, or another research field.