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Remote Database Engineer Jobs in California (NOW HIRING)

Modelyst

Senior Data Engineer

Sacramento, CA · Remote

$113K - $153K/yr

About Modelyst Modelyst is a three-person engineering firm building production data and machine ... Remote within the United States * Must be authorized to work in the U.S. without employer ...

EDO

Senior Data Engineer

Los Angeles, CA · On-site +1

$160K - $190K/yr

... remote work days. To learn more about the work we do at EDO, please visit EDO Press . The Role As a ... What We Are Looking For * 6+ years of data engineering experience and three years of hands-on ...

Quanata

Senior Data Engineer [Remote-US]

San Francisco, CA · Remote

$215K - $300K/yr

The role We're looking for a Senior Data Engineer to help the team deliver data science services ... We are a remote-first company for most positions so you may work from anywhere you like in the U.S ...

Block

Senior Data Engineer, Risk

Bodega Bay, CA · On-site +1

$125K - $170K/yr

Today, Cash App has thousands of employees working globally across office and remote locations ... The Role As a Data Engineer you will handle everything from data architecture and modeling to data ...

Mettle

Laravel Engineer (Remote)

San Francisco, CA · On-site +1

As part of the Engineering team, your time will be spent collaborating with other engineers and ... Good understanding of relational databases (MySQL / Postgres) * API driven development * Ability to ...

Nourish

Senior / Staff Data Engineer

San Francisco, CA · On-site +1

$124K - $169K/yr

About the Role We are hiring a Senior or Staff Data Engineer to become the first dedicated data ... with exceptional remote candidates considered. Our office is located in Gramercy. Key ...

Alutiiq

Software Engineer

San Diego, CA · On-site +1

Develop and maintain secure web interfaces, APIs, databases, and cloud-based applications. Support ... Ability to work independently in a remote environment while supporting geographically distributed ...

Primary.Health

QA Engineer (Remote)

San Francisco, CA · Remote

... and state databases, easing the reporting process. JOB TITLE: QA Engineer JOB TYPE: Full-time LOCATION: Remote JOB SCOPE: As a Quality Engineer at Primary you will be responsible for quality ...

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Remote Database Engineer information

What is the difference between Remote Database Engineer vs Remote Data Analyst?

AspectRemote Database EngineerRemote Data Analyst
Required CredentialsBachelor's in Computer Science, SQL, database certificationsBachelor's in Statistics, Data Science, SQL, Excel skills
Work EnvironmentDeveloping, maintaining, and optimizing databases remotelyAnalyzing data sets, creating reports remotely
Employer & Industry UsageTech, finance, healthcare companies managing data infrastructureMarketing, finance, consulting firms interpreting data trends

Remote Database Engineers focus on building and maintaining databases, requiring technical certifications and programming skills. Remote Data Analysts interpret data to inform business decisions, emphasizing analytical tools and reporting. Both roles are common in tech-driven industries and often overlap in data-related tasks, but they serve different core functions in data management and analysis.

What is a Remote Database Engineer?

A Remote Database Engineer is a professional who designs, implements, maintains, and optimizes database systems while working from a location outside of a traditional office setting. Their responsibilities include ensuring database security, troubleshooting issues, managing backups, and improving performance, all while collaborating with other team members virtually. They often work with a range of database technologies such as SQL, NoSQL, and cloud-based solutions to support business applications and data needs.

How does a Remote Database Engineer typically collaborate with development and operations teams to ensure database reliability?

As a Remote Database Engineer, you'll frequently coordinate with both development and operations teams through virtual meetings, collaborative platforms, and ticketing systems. Your main responsibilities include reviewing schema changes, optimizing queries, and troubleshooting performance issues alongside developers. You'll also work with operations staff to implement backup strategies, monitor database health, and ensure security compliance. Clear communication and proactive documentation are essential for seamless collaboration in a remote environment.

What are the key skills and qualifications needed to thrive as a Remote Database Engineer, and why are they important?

To thrive as a Remote Database Engineer, you need strong expertise in database design, optimization, and management, typically supported by a degree in computer science or a related field. Familiarity with database platforms like MySQL, PostgreSQL, Microsoft SQL Server, and cloud-based systems, along with certifications such as Oracle Certified Professional or AWS Certified Database - Specialty, is highly valued. Excellent problem-solving, communication, and self-management skills are crucial for collaborating across distributed teams and maintaining system reliability. These skills and qualities are important to ensure secure, efficient, and scalable database solutions in a remote work environment.
What are the most commonly searched types of Database Engineer jobs in California? The most popular types of Database Engineer jobs in California are:
What are popular job titles related to Remote Database Engineer jobs in California? For Remote Database Engineer jobs in California, the most frequently searched job titles are:
What job categories do people searching Remote Database Engineer jobs in California look for? The top searched job categories for Remote Database Engineer jobs in California are:
What cities in California are hiring for Remote Database Engineer jobs? Cities in California with the most Remote Database Engineer job openings:
Remote Database Engineer jobs near you
Infographic showing various Remote Database Engineer job openings in California as of June 2026, with employment types broken down into 91% Full Time, 3% Part Time, 1% Temporary, and 5% Contract. Highlights an 38% Physical, 3% Hybrid, and 59% Remote job distribution.

Senior Staff Engineer - AI Data Path

Data Direct Networks

San Francisco, CA • On-site, Remote

$124K - $169K/yr

Other

Posted 27 days ago

Job description

Overview
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.
Job Description
DDN is seeking a highly experienced Senior Staff Engineer specializing in AI Data Path & Storage to lead hands-on development and integration of advanced storage systems with next-generation AI inference pipelines. This role involves coding, prototyping, and rapidly iterating on solutions in close collaboration with architects to design and deliver high-performance data movement architectures. You will leverage NVIDIA's NIXL (Inference Transfer Library) alongside the Infinia Data Intelligence Platform to enable ultra-low-latency, high-throughput data movement across GPU, memory, and distributed storage layers, including workloads involving KV cache management and vector database retrieval. The ideal candidate brings deep expertise in distributed storage, GPU data paths, and large-scale system optimization, with a proven track record of building and shipping production-grade AI infrastructure.
Key Responsibilities
  • Lead the design and implementation of high-performance data movement pipelines using NVIDIA NIXL across GPU, CPU, and storage tiers.
  • Architect and drive integration of DDN Infinia with GPU-accelerated inference platforms for large-scale, real-time AI workloads.
  • Own end-to-end optimization of I/O paths between GPU memory and storage using technologies such as NVIDIA GPUDirect Storage, RDMA, and NVMe-over-Fabrics.
  • Define and implement multi-tier storage architectures (NVMe, SSD, object storage) optimized for inference latency, throughput, and scalability.
  • Lead development of advanced KV cache management strategies, including offloading, prefetching, and persistence across distributed storage layers.
  • Partner with AI/ML engineering teams to optimize inference performance in frameworks such as PyTorch and TensorFlow.
  • Establish benchmarking frameworks and lead performance tuning efforts for storage and data movement in production inference environments.
  • Diagnose and resolve complex system bottlenecks across storage, networking, and GPU subsystems.
  • Influence architecture decisions for distributed inference systems, ensuring scalability, resilience, and efficient data locality.
  • Drive engineering excellence through best practices in observability, performance monitoring, automation, and reliability engineering.
  • Mentor junior engineers and provide technical leadership across cross-functional teams.

Required Qualifications
  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
  • 12+ years of experience in storage systems, distributed systems, or performance engineering.
  • Proven track record of architecting and delivering large-scale, high-performance infrastructure systems.
  • Deep expertise in distributed storage architectures (object storage, scalable file systems, or cloud-native storage platforms).
  • Strong understanding of Linux I/O stack, filesystem internals, and storage protocols.
  • Extensive hands-on experience with NVMe, SSD optimization, and high-performance storage environments.
  • Strong experience with RDMA, InfiniBand, or other high-speed data transfer technologies.
  • Solid understanding of GPU computing concepts and CPU-GPU data movement patterns.
  • Proficiency in Python and/or C/C++, with advanced debugging, profiling, and performance tuning skills.
  • Demonstrated ability to optimize latency-sensitive, high-throughput production systems.

Preferred Skills
  • Hands-on experience with NVIDIA NIXL or similar data movement frameworks.
  • Experience with GPU-aware storage pipelines and GPUDirect Storage.
  • Strong understanding of AI inference systems, LLM serving architectures, and KV cache optimization.
  • Experience with Retrieval-Augmented Generation (RAG) pipelines and open vector search ecosystems.
  • Background in high-performance computing (HPC) or hyperscale distributed environments.
  • Expertise in caching strategies, memory tiering, and data locality optimization.
  • Experience designing disaggregated compute and storage architectures.

What You'll Work On
  • Leading the evolution of storage systems into GPU-native data layers for AI inference
  • Building next-generation distributed AI infrastructure using NIXL and Infinia
  • Driving performance breakthroughs in real-time LLM inference at scale
  • Designing storage architectures for large-scale AI datasets and retrieval systems

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