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Dataops Jobs in California (NOW HIRING)

Data Engineer

San Francisco, CA · On-site

$135K - $190K/yr

Implement DataOps best practices so our data -- and the AI features built on top of it -- stays timely, accurate, and trusted * Collaborate with leadership to define KPIs, build dashboards, and ...

Data Engineer

Foster City, CA · On-site

$180K - $230K/yr

A strong DataOps mindset and opinions on next-generation warehousing tools $180,000 - $230,000 a year Base Salary Range There are three major components to compensation for this position: salary ...

Senior Database Engineer

San Francisco, CA · Hybrid

$124K - $169K/yr

At least basic knowledge and some hands-on implementation of CI/CD pipelines and DataOps practices. * You have experience with data governance, compliance, and lifecycle management. * You have strong ...

Data Engineer

Los Angeles, CA · On-site

$123K - $148K/yr

... DataOps concepts and operating in cross-functional teams that include data engineering personas. * The measures of success for this role include delivering data pipelines with trusted, quality data ...

Knowledge of DevOps/DataOps practices including CI/CD, infrastructure as code (Terraform, CloudFormation), and containerization (Docker, Kubernetes) * Experience with real-time streaming ...

Data Engineer

Foster City, CA

$133K - $160K/yr

A strong DataOps mindset and opinions on next-generation warehousing tools Base Salary Range There are three major components to compensation for this position: salary, Amazon Restricted Stock Units ...

Data Engineer

San Diego, CA

$121K - $146K/yr

... DataOps concepts and operating in cross-functional teams that include data engineering personas. * The measures of success for this role include delivering data pipelines with trusted, quality data ...

Staff Data Architect

Long Beach, CA · On-site

$69.50 - $89.50/hr

... s/DataOps practices including CI/CD, infrastructure as code (Terraform, CloudFormation), and containerization (Docker, Kubernetes) • Experience with real-time streaming architectures and event ...

At Hive, our DataOps team is responsible for supporting the development of our proprietary AI models leveraging our Hive Data platform to deliver high-quality training and testing datasets. Day to ...

Senior Data Governance Professional

Irvine, CA · Hybrid

$113K - $154K/yr

Roll out and integrate governance processes with enterprise workflows, including MLOps, DataOps, PMO, and agile software development life cycles. * Establish robust change management processes to ...

Data Engineer

San Diego, CA

$121K - $146K/yr

Experience with DataOps or similar mission-critical pipeline automation (e.g., deduplication, schema normalization). * Any experience leveraging universal data distribution architectures within DOD ...

... DataOps. Delivered as a SaaS solution, Acceldata is trusted by leading global organizations such as HPE, HSBC, Visa, Freddie Mac, Manulife, Workday, Oracle, PubMatic, PhonePe (Walmart), Hershey ...

Data Engineer

San Diego, CA · On-site

$122K - $147K/yr

Experience with DataOps or similar mission-critical pipeline automation (e.g., deduplication, schema normalization). * Any experience leveraging universal data distribution architectures within DOD ...

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Dataops information

See California salary details

$12

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$35

How much do dataops jobs pay per hour?

As of Jun 9, 2026, the average hourly pay for dataops in California is $22.83, according to ZipRecruiter salary data. Most workers in this role earn between $17.31 and $23.70 per hour, depending on experience, location, and employer.

What are DataOps?

DataOps, short for Data Operations, is a set of practices, processes, and technologies that combine data engineering, data integration, and DevOps methodologies to improve the quality and speed of data analytics. DataOps aims to streamline the flow of data from source to value, enabling organizations to deliver reliable, high-quality data to stakeholders more efficiently. This approach emphasizes collaboration, automation, and monitoring throughout the data lifecycle to reduce errors and shorten development cycles. The ultimate goal of DataOps is to create an agile data pipeline that adapts quickly to changing business needs.

What is the difference between Dataops vs Data Engineer?

AspectDataopsData Engineer
Primary FocusAutomating data workflows, deployment, and operational efficiencyBuilding and maintaining data pipelines, storage, and infrastructure
Skills & CertificationsDevOps tools, scripting, cloud platforms, CI/CD practicesSQL, ETL tools, cloud platforms, programming (Python, Scala)
Work EnvironmentCollaborates with DevOps, data teams, and operationsWorks closely with data scientists, analysts, and infrastructure teams
Industry UsageUsed in organizations focusing on data deployment and automationUsed in data infrastructure development and data pipeline creation

While both Dataops and Data Engineers work with data infrastructure, Dataops emphasizes automation, deployment, and operational efficiency, whereas Data Engineers focus on building and maintaining data pipelines and storage systems. Understanding these differences helps organizations assign the right roles for their data needs.

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

To thrive as a DataOps Engineer, you need expertise in data engineering, automation, cloud platforms, and a solid understanding of CI/CD pipelines, typically backed by a degree in computer science or related fields. Familiarity with tools like Apache Airflow, Kubernetes, Docker, Jenkins, and cloud services such as AWS, GCP, or Azure is commonly required, along with knowledge of scripting languages like Python or Bash. Strong collaboration, problem-solving, and communication skills help DataOps professionals work effectively across data, development, and operations teams. These abilities ensure reliable, scalable, and efficient data infrastructure, enabling organizations to quickly deliver high-quality data solutions.

How does a DataOps professional typically collaborate with data engineers, analysts, and other IT teams?

DataOps professionals play a key role in bridging the gap between data engineering, analytics, and IT by facilitating efficient, automated workflows and ensuring data quality across the pipeline. They often work closely with data engineers to streamline data integration and deployment processes, while collaborating with analysts to support timely access to reliable data. Regular communication and cross-functional teamwork are essential, as DataOps is responsible for implementing best practices that help different teams deliver insights faster and with fewer errors. This collaborative environment also encourages continuous feedback and process improvement.
What job categories do people searching Dataops jobs in California look for? The top searched job categories for Dataops jobs in California are:
What cities in California are hiring for Dataops jobs? Cities in California with the most Dataops job openings:
Infographic showing various Dataops job openings in California as of June 2026, with employment types broken down into 87% Full Time, and 13% Contract. Highlights an 62% In-person, and 38% Remote job distribution, with an average salary of $47,480 per year, or $22.8 per hour.
Data Architect

$75 - $96.50/hr

Full-time

Medical, Life, Retirement, PTO

Posted 21 days ago


Job description

CompanyFederal Reserve Bank of St. LouisThe St Louis Fed is one of 12 Reserve Banks serving all or parts of Missouri, Illinois, Indiana, Kentucky, Tennessee, Mississippi, and Arkansas with branches in Little Rock, Louisville and Memphis. The St. Louis Fed's most critical functions include promoting stable prices and economic growth, fostering a sound financial system, providing payment services to financial institutions, supporting the U.S. Treasury's financial operations, and advancing economic education, community development and fair access to credit. The Bank strives to maintain an engaging and exciting work environment that is both inviting and collegial.

The Data Architect will lead the design and modernization of the data architecture that powers the economic data platforms of St. Louis based Research applications such as FRED. These platforms manage massive collections of economic time-series data, historical revisions, digitized archival documents, and research publications.

This role focuses on designing scalable data platforms, data models, and data governance frameworks to support long-term growth, advanced analytics, and global access to economic data. It will leverage in-depth knowledge of modern data technologies, industry frameworks, data security best practices and emerging innovations in AI/ML and data science to accelerate value, delivery and outcomes for the business.

The Data Architect will partner closely with the Application/Enterprise Architect to ensure seamless integration between data platforms and application services.

Responsibilities

  • Define and evolve the target data architecture supporting economic data systems.
  • Design scalable storage architectures capable of supporting billions of time-series observations and historical revisions.
  • Develop metadata schemas supporting dataset discoverability, lineage, and governance.
  • Standardize dataset structures and metadata across multiple platforms.
  • Implement scalable data processing frameworks capable of supporting growing dataset volumes.
  • Improve indexing and metadata strategies that support dataset search and discovery.
  • Enable advanced analytical capabilities for researchers and developers.
  • Partner with the Application Architect to optimize data access patterns for APIs and applications.

Qualifications

  • 7+ years of experience in data architecture, data engineering or database design and large-scale enterprise cloud data implementations in complex, highly regulated environments. Deep understanding of modern data technology stacks, cloud data platforms (AWS preferred), and enterprise software solutions.
  • Demonstrated experience designing, architecting and supporting external / public-facing applications with a strong emphasis on scalability, security, availability and performance for external customer-facing platforms. Demonstrated knowledge of and leading adoption of industry best practices in the areas of DataOps and modern data stack tools, data governance, SQL and other query tools and knowledge of data privacy regulations. Industry-related certifications in one or more of the above areas are desired.
  • Demonstrated experience in cloud data architecture skills including designing, architecting and delivering modern cloud data platforms to ingest, process, store and expose data across the enterprise. Expert knowledge of data modeling techniques and tools, data lifecycle management and integration patterns to ensure that data flows are consistent, reliable and reusable across services and solutions. Experience with data storage technologies, partitioning strategies, caching, data access patterns, and robust security strategies enforcing privacy and regulatory requirements including designing standardized approaches for data classification, access control, encryption, retention and auditability. Knowledge of data warehousing concepts and tools, big data technologies, machine learning and AI data requirements.
  • Outstanding communication and collaboration skills, including translating technical topics and risks into business teams. Ability to personalize communication to audience from technologists to executive leadership.
  • Extensive, in-depth experience implementing highly complex technology projects in a cross-functional matrix environment with demonstrated ability to drive consensus and deliver results. Examples of leading through influence and successfully resolving conflicting priorities are required.
  • US Citizenship required
  • Lesser experience might be considered for a lesser grade

Preferred Qualifications

  • Experience working with time-series data platforms or analytical datasets.
  • Experience with distributed query engines and large-scale data processing systems.
  • Experience with data catalog and metadata management platforms.
  • Familiarity with economic datasets or research data environments.
  • Experience supporting public data access or research-oriented platforms.

Total Rewards

Bring your passion and expertise, and we'll provide the opportunities that will challenge you and propel your growth-along with a wide range of benefits and perks that support your health, wealth, and life.

Salary: $140-170k

In addition to competitive compensation, we offer a comprehensive benefits package that all brought together in a flexible work environment where you can truly find balance:

  • Generous paid time off
  • Tuition & Training assistance/reimbursement
  • 401(k) match & Annuity/Pension fund
  • Top-notch health care benefits
  • Child and family care leave
  • Professional development opportunities
  • And more...

At the Federal Reserve Bank of St. Louis, we are committed to a strong and resilient economy for all. We prioritize inclusion and strive to be a workplace where all employees can thrive. Learn more about Bank's culture

The Federal Reserve Bank of St Louis is an Equal Opportunity Employer.

Full Time / Part TimeFull timeRegular / TemporaryRegularJob Exempt (Yes / No)YesJob CategoryInformation Technology Family GroupWork ShiftFirst (United States of America)

The Federal Reserve Banks are committed to equal employment opportunity for employees and job applicants in compliance with applicable law and to an environment where employees are valued for their differences.

Always verify and apply to jobs on Federal Reserve System Careers (https://rb.wd5.myworkdayjobs.com/FRS) or through verified Federal Reserve Bank social media channels.

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