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Dataops Jobs in California (NOW HIRING)

NextData

Senior Sales Engineer

San Francisco, CA · On-site

Experience with AI/ML platforms , MLOps, DataOps or developer platforms * Cloud and data engineering certifications * Public speaking or thought leadership experience in data infrastructure or ...

Vast

Staff Data Architect

Long Beach, CA

$155K - $221K/yr

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

Stuut

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 ...

Federal Reserve System

Data Architect

San Francisco, CA · On-site

$140/hr

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 ...

New

ICW Group

Data Operations Manager

San Diego, CA · On-site

... DataOps, CI/CD, release management and operational automation practices. • Familiarity with enterprise data governance, metadata management, data quality and security frameworks. • Strong ...

Hitachi

Director, Solutions Marketing

Santa Clara, CA · On-site +1

Expertise in software and data, including structured and unstructured data, DataOps, ETL, and data analysis/reporting. * Familiarity with storage technologies and cybersecurity is a plus. * Skills

Hive

Data Operations Analyst

San Francisco, CA · On-site

$60K - $85K/yr

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 ...

Cotality

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 ...

Vast

Staff Data Architect

Long Beach, CA · On-site

$67 - $86.25/hr

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

TEKsystems

Product Manager

San Diego, CA

... DataOps and CI/CD practices within the team. Lead the automation of deployment, testing, and monitoring to accelerate delivery speed and ensure data quality • Provides technical leadership and ...

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All JobsDataops JobsDataops Jobs in California

Dataops information

See California salary details

$12

$22

$35

How much do dataops jobs pay per hour?

As of Jul 4, 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 are popular job titles related to Dataops jobs in California? For Dataops jobs in California, the most frequently searched job titles are:
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:
Dataops jobs near you
Infographic showing various Dataops job openings in California as of June 2026, with employment types broken down into 81% Full Time, and 19% Contract. Highlights an 74% In-person, and 26% Remote job distribution, with an average salary of $47,480 per year, or $22.8 per hour.
VP, West Coast Delivery - Data, AI & Enterprise Transformation

VP, West Coast Delivery - Data, AI & Enterprise Transformation

EPAM Systems

San Francisco, CA • On-site

Other

Posted 12 days ago

Job description

We are seeking a Head of San Francisco Bay Area/Data, AI & Enterprise Transformation who is native to the Bay Area technology ecosystem - deeply fluent in enterprise-scale data platforms, AI-native engineering, and frontier AI adoption - and ready to build EPAM's most technically ambitious delivery practice on the West Coast. This leader owns delivery excellence across flagship enterprise accounts in the San Francisco-Silicon Valley corridor, leads the buildout of EPAM's Data & AI delivery capability in the Bay Area (a deliberate strategic priority), and serves as EPAM's most senior technical delivery authority with CTO, CPTO, and CDO-level clients who expect a peer, not a vendor. Req.#860823922 Responsibilities Own the Bay Area enterprise portfolio.

Lead delivery across EPAM's flagship accounts in the SF/Silicon Valley corridor. Serve as the most senior delivery voice in client rooms - from data architecture design and AI program scoping through production handoff and account expansion Scale and connect to Data & AI practice. Establish and grow EPAM's Data Platform and AI/ML delivery capability in the Bay Area Define the delivery model, hire the senior talent, and land the $10M+ data transformation programs Front-face transformation.

Drive change at CTO, CPTO, and CDO level - representing delivery architecture, data platform strategy, AI adoption roadmaps, and enterprise transformation business cases. Be the person clients trust in the room when the program is under pressure Leverage and enable the frontier AI ecosystem. Translate frontier AI capabilities - from foundation model partners, lab-adjacent ISVs, and hyperscaler AI platforms - into enterprise-grade delivery programs.

Build EPAM's reputation as the integrator that can take frontier AI from prototype to production at enterprise scale Build the talent. Develop, and retain AI-native and data/cloud-native delivery professionals in the Bay Area. Define what AI-native, cloud/data-native delivery means at EPAM West Coast and hold the bar FDEs/Forward Agentic Engineers leader and business enabler Requirements Enterprise delivery track record.

Has led large-scale programs ($15M-$50M+ TCV) with complex client organizations - multi-stakeholder, multi-geography, multi-year. Fully cloud-native, AI-native thinking across the delivery lifecycle. Can point to outcomes: delivery velocity, data quality, AI adoption rates Data platform depth.

Has run data engineering, data platform, or AI/ML engineering delivery at enterprise scale. Fluent in modern data stacks: Databricks, Snowflake, Spark or equivalent. Understands DataOps, MLOps, and the gap between a working model and a production data product AI-native delivery fluency.

Structural AI integration in delivery - autonomous testing, LLM-assisted development, agentic QA, AI observability - not tool familiarity. Can design and defend the AI-native delivery model to a CTO who has heard every pitch Bay Area market gravitas. Active network at Fortune 500 tech, fintech, biotech/life sciences, or enterprise SaaS in the Bay Area.

Carries the credibility and presence to run a room at CPTO or CDO level. Clients trust this person with difficult conversations Frontier AI fluency. Understands the frontier AI landscape - capabilities, limitations, enterprise applicability, and the gap between a lab demo and a production system.

Ideally has relationships at AI labs, AI teams, or frontier-model ISVs 15+ years in software or data delivery leadership at a technology company, consultancy, or systems integrator - with at least 3 years in a Sr. Director/VP or equivalent delivery leadership role on programs of $15-50M+ scope. Must have managed distributed offshore/nearshore delivery teams

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