1

Data Storage Jobs in California (NOW HIRING)

CA · On-site

DDN is the de facto name for AI Storage in high performance environments" - Marc Hamilton, VP, Solutions Architecture & Engineering | NVIDIA DDN is the global leader in AI and multi-cloud data ...

DDN is the de facto name for AI Storage in high performance environments" - Marc Hamilton, VP, Solutions Architecture & Engineering | NVIDIA DDN is the global leader in AI and multi-cloud data ...

DDN is the de facto name for AI Storage in high performance environments" - Marc Hamilton, VP, Solutions Architecture & Engineering | NVIDIA DDN is the global leader in AI and multi-cloud data ...

Data Engineer

San Francisco, CA · On-site

$134K - $162K/yr

This role involves ensuring efficient and accurate data storage, enabling analytics for platform usage, and contributing to data-driven decisions. Responsibilities : • Design and maintain database ...

New

CA · On-site

$124K - $169K/yr

DDN is the de facto name for AI Storage in high performance environments" - Marc Hamilton, VP, Solutions Architecture & Engineering | NVIDIA DDN is the global leader in AI and multi-cloud data ...

CA

$124K - $169K/yr

DDN is the de facto name for AI Storage in high performance environments" - Marc Hamilton, VP, Solutions Architecture & Engineering | NVIDIA DDN is the global leader in AI and multi-cloud data ...

The Senior Storage Engineer will be a part of the data center support group, tasked w/ configuring SAN/NAS systems, managing backup solutions, & maintaining the security of the data center.

AWS Data Engineer

San Francisco, CA · On-site

$134K - $162K/yr

Data Storage Solutions: Design and maintain storage solutions using Medallion Architecture in S3 and Redshift * Workflow Orchestration: Monitor and optimize data workflows using Airflow or other ...

next page

Showing results 1-20

Data Storage information

See California salary details

$14

$36

$107

How much do data storage jobs pay per hour?

As of Jun 28, 2026, the average hourly pay for data storage in California is $36.94, according to ZipRecruiter salary data. Most workers in this role earn between $16.35 and $39.86 per hour, depending on experience, location, and employer.

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 job makes $10,000 a month without a degree?

In data storage and related fields, roles such as cloud solutions architect or senior data engineer can earn $10,000 or more per month, often requiring extensive experience, technical skills, and certifications like AWS or Google Cloud. These positions typically involve managing large-scale data infrastructure and may not require a traditional degree but do demand specialized knowledge and hands-on expertise.

What jobs pay 500,000 a year in the US?

In the field of data storage, high-paying roles such as Chief Data Officer, Data Storage Architect, or senior data infrastructure executives can reach or exceed $500,000 annually, especially in large corporations or tech companies. These positions typically require extensive experience, advanced certifications, and expertise in data management, cloud storage solutions, and enterprise infrastructure. Compensation at this level often includes bonuses, stock options, and other incentives.

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.

What profession makes $400,000 a year?

In the field of data storage, senior roles such as Data Storage Architects or Chief Data Officers can earn $400,000 or more annually, especially with extensive experience, advanced certifications, and leadership responsibilities. These positions often require expertise in data management, storage solutions, and industry standards, and may involve overseeing large-scale infrastructure or strategic planning.

What jobs make $1,000,000 a year?

In the field of data storage, high-paying roles such as Chief Data Officer, Chief Technology Officer, or senior executive positions in large technology companies can earn over $1 million annually, often including bonuses and stock options. These roles typically require extensive experience, advanced technical skills, and leadership responsibilities in managing data infrastructure and strategy.

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 most commonly searched types of Data Storage jobs in California? The most popular types of Data Storage jobs in California are:
What cities in California are hiring for Data Storage jobs? Cities in California with the most Data Storage job openings:

Data Scientist/ Data Architect

Data Direct Networks

CA • On-site

Full-time

Posted 5 days ago


Job description

This is an incredible opportunity to be part of a company that has been at the forefront of AI and high-performance data storage innovation for over two decades. DataDirect Networks (DDN) is a global market leader renowned for powering many of the world's most demanding AI data centers, in industries ranging from life sciences and healthcare to financial services, autonomous cars, Government, academia, research and manufacturing.

"DDN's A3I solutions are transforming the landscape of AI infrastructure." – IDC 

 

“The real differentiator is DDN. I never hesitate to recommend DDN. DDN is the de facto name for AI Storage in high performance environments” - Marc Hamilton, VP, Solutions Architecture & Engineering | NVIDIA 

DDN is the global leader in AI and multi-cloud data management at scale. Our cutting-edge data intelligence platform is designed to accelerate AI workloads, enabling organizations to extract maximum value from their data. With a proven track record of performance, reliability, and scalability, DDN empowers businesses to tackle the most challenging AI and data-intensive workloads with confidence. 

Our success is driven by our unwavering commitment to innovation, customer-centricity, and a team of passionate professionals who bring their expertise and dedication to every project. This is a chance to make a significant impact at a company that is shaping the future of AI and data management. 

Our commitment to innovation, customer success, and market leadership makes this an exciting and rewarding role for a driven professional looking to make a lasting impact in the world of AI and data storage. 


DDN is the global leader in AI and data intelligence infrastructure, powering many of the world's most demanding AI, HPC, and data-intensive environments. Our customers include leading enterprises, research institutions, government agencies, and AI innovators that rely on DDN technology to accelerate discovery, innovation, and business outcomes.

We are seeking a highly motivated Data Scientist / Data Architect to join our team and help shape the future of data-driven products, AI platforms, and enterprise analytics. This role combines data science, machine learning, data engineering, and enterprise architecture to deliver scalable solutions that transform data into strategic business value.

Position Summary

As a Data Scientist / Data Architect, you will work at the intersection of AI, data platforms, cloud infrastructure, and business strategy. You will design and implement modern data architectures while developing analytics and machine learning solutions that support operational excellence, customer success, product innovation, and business growth.

The ideal candidate combines strong technical depth in data science and architecture with the ability to engage stakeholders, translate business requirements into technical solutions, and drive projects from concept through production deployment.

 

Key Responsibilities

Data Science & Analytics

  • Develop machine learning and AI solutions to solve business and operational challenges.
  • Design, build, validate, and deploy models for forecasting, anomaly detection, customer analytics, capacity planning, and product intelligence.
  • Apply statistical analysis and experimentation techniques to generate actionable insights.
  • Develop dashboards, visualizations, and executive-level reporting to communicate findings and recommendations.
  • Monitor model performance and support continuous improvement initiatives.
  • Partner with business stakeholders to define key metrics, KPIs, and success measures across products and operations.
  • Design scalable enterprise data architectures supporting structured, semi-structured, and unstructured data workloads.
  • Define data models, metadata standards, governance frameworks, and architectural best practices.
  • Architect modern data platforms leveraging cloud, hybrid-cloud, lakehouse, and distributed data technologies.
  • Establish data integration strategies across CRM, ERP, product usage, support, operational, and business systems.
  • Build scalable ETL/ELT pipelines and data services that support analytics and AI workloads.
  • Drive adoption of data quality, lineage, security, privacy, and compliance standards.

AI & Data Product Development

  • Partner with product, engineering, and business leaders to identify high-value AI and analytics opportunities.
  • Build reusable data products, semantic layers, and self-service analytics capabilities.
  • Support AI initiatives involving LLMs, RAG architectures, vector databases, and enterprise knowledge systems.
  • Collaborate with software engineering teams to operationalize analytics and AI capabilities in production environments.
  • Contribute to the development of intelligent platform features that improve customer experience and operational efficiency.

Leadership & Cross-Functional Collaboration

  • Serve as a trusted advisor on data strategy, architecture, and analytics best practices.
  • Lead technical design reviews and architecture discussions.
  • Mentor data scientists, data engineers, and analysts.
  • Partner with stakeholders across Product, Engineering, Operations, Customer Success, Finance, and Executive Leadership.
  • Communicate technical concepts and recommendations to both technical and non-technical audiences.

Required Qualifications

  • Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Applied Mathematics, Engineering, or a related field.
  • 8+ years of experience in data science, data architecture, analytics engineering, or related disciplines.
  • Strong proficiency in Python and SQL.
  • Experience building and deploying machine learning models in production environments.
  • Deep understanding of data modeling, ETL/ELT pipelines, and modern data platform architectures.
  • Experience with cloud platforms such as AWS, Azure, or Google Cloud.
  • Hands-on experience with distributed data processing technologies such as Spark, Databricks, Snowflake, BigQuery, or equivalent platforms.
  • Strong knowledge of statistics, experimentation, forecasting, and predictive analytics.
  • Excellent communication and stakeholder management skills.
  • Experience working with AI platforms, cloud infrastructure, SaaS products, or large-scale distributed systems.
  • Experience with MLOps, DataOps, CI/CD, and model lifecycle management.
  • Familiarity with vector databases, retrieval systems, LLMs, and generative AI architectures.
  • Experience with Kubernetes, containerized environments, and cloud-native platforms.
  • Knowledge of data governance, security, privacy, and regulatory frameworks.
  • Experience leading enterprise-scale data transformation initiatives.

Salary Range for this role: $215,000 - $265,000


Join our dynamic and driven team, where engineering excellence is at the heart of everything we do. We seek individuals who love to challenge themselves and are fueled by curiosity. Here, you'll have the opportunity to work across various areas of the company, thanks to our flat organizational structure that encourages hands-on involvement and direct contributions to our mission. Leadership is earned by those who take initiative and consistently deliver outstanding results, both in their work ethic and deliverables, making strong prioritization skills essential. Additionally, we value strong communication skills in all our engineers and researchers, as they are crucial for the success of our teams and the company as a whole.

Interview Process: After submitting your application, one of our recruiters will review your resume. If your application passes this stage, you will be invited to a 30-minute interview during which a member of our team will ask some basic questions. If you clear the interview, you will enter the main process, which can consist of up to four interviews in total:

  • Coding assessment: Often in a language of your choice.
  • Systems design: Translate high-level requirements into a scalable, fault-tolerant service (depending on role).
  • Real-time problem-solving: Demonstrate practical skills in a live problem-solving session.
  • Meet and greet with the wider team.
  • Our goal is to finish the main process in 2-3 weeks at most.

DataDirect Networks (DDN) is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity, gender expression, transgender, sex stereotyping, sexual orientation, national origin, disability, protected Veteran Status, or any other characteristic protected by applicable federal, state, or local law.

#LI-Remote