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Data Jobs in California (NOW HIRING)

Data Direct Networks

CA · On-site

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 ...

Data Direct Networks

CA · On-site

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 ...

H5 Data Centers

Data Center Project Manager

Sunnyvale, CA · On-site

$125K - $130K/yr

Ensure the effective and economical use of H5 Data Center's business resources, and to support the financial requirements of the operation at the Data Center facilities. Works to make sure proper ...

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All JobsData JobsData Jobs in California

Data information

See California salary details

$45.4K

$162.9K

$240.3K

How much do data jobs pay per year?

As of Jul 7, 2026, the average yearly pay for data in California is $162,857.00, according to ZipRecruiter salary data. Most workers in this role earn between $131,800.00 and $167,800.00 per year, depending on experience, location, and employer.

What do data jobs do?

Data jobs involve collecting, analyzing, and interpreting data to help organizations make informed decisions. Roles such as data analysts and data scientists use tools like SQL, Python, or R to process large datasets and generate insights. These jobs often require strong analytical skills and knowledge of data management and visualization techniques.

What are data jobs?

Data jobs refer to roles that involve collecting, processing, analyzing, and interpreting data to support business decisions or research. These jobs can include positions such as data analyst, data scientist, data engineer, and database administrator. Professionals in this field use statistical techniques, programming, and data visualization tools to derive insights from large datasets. Data jobs are in high demand across various industries, including finance, healthcare, technology, and marketing.

What are the key skills and qualifications needed to thrive as a Data Analyst, and why are they important?

To thrive as a Data Analyst, you need strong analytical skills, proficiency in statistics, and a solid foundation in mathematics, typically supported by a degree in a quantitative field. Familiarity with data analysis tools like Excel, SQL, Python, and visualization platforms such as Tableau or Power BI is often required, and certifications in these tools can be advantageous. Attention to detail, critical thinking, and effective communication skills help analysts interpret data accurately and present actionable insights to stakeholders. These skills are crucial for transforming raw data into meaningful information that drives informed business decisions.

How does a Data Analyst typically collaborate with other departments within an organization?

Data Analysts frequently work cross-functionally, partnering with teams such as marketing, finance, operations, and product development. They gather requirements from stakeholders, interpret data to provide actionable insights, and often present findings in meetings or reports tailored to the audience's needs. Effective communication is key, as analysts must translate complex data into clear, impactful recommendations that guide business decisions. This collaborative environment fosters both learning and professional growth, as Data Analysts gain exposure to various business functions.

What Are Different Jobs That Work With Data?

Many different jobs require you to work with data. Occupational health and safety engineers, for instance, assess safety data collected by technicians and specialists and then design new processes to mitigate observed risks. Many careers in medical research, such as running clinical trials or developing new pharmaceuticals, require data collection and analysis. A large number of government labor and economic forecasting positions employ statisticians who analyze and model data based on surveys or raw information, such as the census or employment records.

What is the definition of data?

Data in a data-related job refers to raw, unprocessed facts and figures collected for analysis, decision-making, or processing. It can include numbers, text, images, or other information stored and managed using tools like databases and data analysis software. Understanding data is essential for tasks such as data cleaning, interpretation, and reporting.

What are careers in data?

Careers in data include roles such as data analyst, data scientist, data engineer, and database administrator. These jobs involve collecting, analyzing, and interpreting data to support decision-making, often requiring skills in programming, statistics, and data visualization tools like SQL, Python, or R.

What is the difference between Data vs Data Analyst?

AspectDataData Analyst
Required CredentialsTypically a degree in computer science, information technology, or related fieldsSame as Data, often requiring a degree in statistics, data science, or related areas
Work EnvironmentData professionals work in IT, data engineering, or database management settingsData analysts work in business, finance, marketing, and similar industries analyzing data for insights
Employer & Industry UsageUsed across tech, finance, healthcare, and more for data management and infrastructureCommonly employed in business sectors to interpret data and support decision-making

Data professionals focus on managing, storing, and processing data, while Data Analysts interpret and analyze data to generate insights. Both roles require similar educational backgrounds but differ in their primary functions within organizations.

What skills are needed for data jobs?

Data jobs typically require strong analytical skills, proficiency in programming languages such as Python or R, and knowledge of database management and SQL. Familiarity with data visualization tools like Tableau or Power BI and understanding of statistical methods are also important. Additionally, problem-solving abilities and attention to detail are essential for success in this field.

What are the 4 types of data?

In data-related jobs, the four main types of data are structured data, which is organized in databases and spreadsheets; unstructured data, such as emails, videos, and social media content; semi-structured data, like XML or JSON files that have some organization; and metadata, which provides information about other data. Understanding these types helps data professionals manage, analyze, and interpret data effectively using tools like SQL, Python, or data visualization software.

What is data on my phone?

Data on your phone refers to the digital information stored or transmitted by your device, including apps, files, and internet activity. For a data-related job, understanding how data is collected, managed, and secured is essential, often involving skills in data analysis, database management, and cybersecurity. Managing phone data may also require knowledge of mobile operating systems and data privacy practices.

What are the synonyms of data?

For a data analyst or data scientist, synonyms of data include information, figures, statistics, metrics, and records. These terms are often used interchangeably depending on the context and type of data being handled, and familiarity with data management tools like SQL or Excel can aid in working with these concepts.

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

High-paying jobs that can reach or exceed $500,000 annually include roles such as senior investment bankers, hedge fund managers, specialized surgeons, and top executives like CEOs and CFOs. These positions often require extensive experience, advanced degrees, and strong industry networks, with compensation frequently including bonuses and stock options.
More about Data jobs
What are the most commonly searched types of Data jobs in California? The most popular types of Data jobs in California are:
What are popular job titles related to Data jobs in California? For Data jobs in California, the most frequently searched job titles are:
What job categories do people searching Data jobs in California look for? The top searched job categories for Data jobs in California are:
What cities in California are hiring for Data jobs? Cities in California with the most Data job openings:
Data jobs near you
Infographic showing various Data job openings in California as of July 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $162,857 per year, or $78.3 per hour.

Data Scientist/ Data Architect

Data Direct Networks

San Francisco, CA • On-site, Remote

Full-time

This job post has expired today. Applications are no longer accepted.

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 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
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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