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Dataops Jobs in California (NOW HIRING)

AllSTEM Connections

IT Solutions Engineer IV

Oakland, CA · On-site

$166K - $235K/yr

Strong familiarity with DataOps/DevOps practices and their application to data platform management. Equal Opportunity Employer / Disabled / Protected Veterans The Know Your Rights poster is available ...

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 ...

Persistent Systems

Delivery Head

Sunnyvale, CA · On-site

$252K/yr

... DataOps across cloud environments. Client & Account Leadership • Serve as the senior delivery point of contact for Hi-Tech clients, building durable, trust-based relationships with client ...

Vast

Senior Data Engineer

Long Beach, CA · On-site

$111K - $151K/yr

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

Ventura Foods

Senior DevOps Engineer

Irvine, CA · Hybrid

$130K - $171K/yr

Work within Agile/Scrum frameworks using Jira and follow ITIL change management processes via ServiceNow. * DevOps Strategy & Transformation Lead and drive DevOps, DataOps, and ML/AI Ops initiatives ...

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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 Sep 7, 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 is a 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.

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 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.

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 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 August 2026, with employment types broken down into 88% Full Time, 6% Part Time, and 6% Contract. Highlights an 68% Physical, 11% Hybrid, and 21% Remote job distribution, with an average salary of $47,480 per year, or $22.8 per hour.

IT Solutions Engineer IV

AllSTEM Connections

Oakland, CA • On-site

$166K - $235K/yr

Temporary

Medical, Dental, Vision, Retirement

Re-posted 26 days ago

Key responsibilities

  • Manage the full project lifecycle of complex data-driven projects, including planning, resource allocation, and operational rollout of data pipelines.

  • Oversee the design, implementation, and governance of modern data platform architectures, ensuring compliance with data standards and quality requirements.

  • Collaborate with technical teams to deploy data management solutions and ensure the platform supports AI/ML use cases.

Job description

Job Title: Senior Data Platform Delivery Manager
Role Overview
We are seeking a Senior Data Platform Delivery Manager to spearhead the implementation of our next-generation enterprise data ecosystem. You will serve as the strategic bridge between business stakeholders and technical engineering teams, ensuring that our data platform strategy-spanning cloud warehousing, governance, and quality management-is delivered on time, within budget, and to the highest architectural standards.
This is a high-visibility, "hands-on leadership" role. You will own the full project lifecycle, from program planning and resource allocation to the operational rollout of complex data pipelines. If you are an expert at navigating the intersection of Agile/Waterfall delivery and modern data engineering, this is an excellent opportunity to shape the data foundation of a large-scale enterprise.
Key Responsibilities
Program Leadership & Delivery
• Project Lifecycle: Manage complex technology projects from inception through production. Lead cross-functional teams in the delivery of cloud-native data platforms, ensuring tight integration between data engineering, governance, and business intelligence.
• Governance & Strategy: Define and enforce data governance frameworks, including Metadata Management, Lineage, and Data Quality standards. Ensure all solutions adhere to compliance and privacy requirements.
• Planning & Governance: Oversee budget, resource management, and risk/dependency mapping. Utilize Agile/Scrum or Waterfall frameworks to manage delivery velocity and project health.
Technical Architectural Oversight
• Platform Development: Oversee the design and implementation of modern Data Warehouse/Lakehouse architectures. Ensure best practices in ETL/ELT development, data modeling, and pipeline orchestration.
• Quality & Integration: Partner with technical teams to deploy Master Data Management (MDM) solutions that drive data consistency and reliability across the enterprise.
• AI/ML Enablement: Collaborate with data scientists and engineers to ensure the platform is architected for future-ready AI/ML use cases.
Qualifications & Requirements
Minimum Qualifications
• Education: Bachelor's degree in CS, Information Systems, Engineering, or Data Science (Master's preferred).
• Experience Baseline: 8+ years managing complex data-driven projects; 5+ years leading enterprise data platform implementations.
• Technical Mastery: Proven success delivering projects involving Snowflake and large-scale cloud data ecosystems.
• Process Mastery: Deep experience with Data Engineering (ETL/ELT), Master Data Management (MDM), and Data Quality Management.
Preferred Attributes
• Certifications: PMP, PgMP, Scrum Master, or SAFe Agilist.
• Industry Experience: Proven success in large-scale regulated industries (Financial Services, Healthcare, Energy, etc.).
• Operations: Strong familiarity with DataOps/DevOps practices and their application to data platform management.
Equal Opportunity Employer / Disabled / Protected Veterans
The Know Your Rights poster is available here:
https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12.pdf
The pay transparency policy is available here:
https://www.dol.gov/sites/dolgov/files/ofccp/pdf/pay-transp_%20English_formattedESQA508c.pdf
For temporary assignments lasting 13 weeks or longer, AllSTEM Connections is pleased to offer major medical, dental, vision, 401k and any statutory sick pay where required.
We are committed to working with and providing reasonable accommodations to individuals with disabilities. If you need a reasonable accommodation for any part of the employment process, please contact your staffing representative who will reach out to our HR team.
AllSTEM Connections participates in the E-Verify program in certain locations as required by law. Learn more about the E-Verify program.
https://e-verify.uscis.gov/web/media/resourcesContents/E-Verify_Participation_Poster_ES.pdf
We also consider for employment qualified applicants regardless of criminal histories, consistent with legal requirements, including, if applicable, the City of Los Angeles' Fair Chance Initiative for Hiring Ordinance. Pursuant to applicable state and municipal Fair Chance Laws and Ordinances, we will consider for employment-qualified applicants with arrest and conviction records, including, if applicable, the San Francisco Fair Chance Ordinance. For Los Angeles, CA applicants: Qualified applications with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.
Additional Skills
(none specified)
AllSTEM Representative Contact Info
Account Executive:
Nichols
Branch Phone:
(909) 244-1777
Location:
Ontario, CA

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