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Data Ops Engineer Jobs in California (NOW HIRING)

SAIC

Data Ops Engineer

San Diego, CA · On-site +1

$200K - $240K/yr

ORA_ON_SITE Description We are seeking a Data Ops Engineer to design, build, and maintain real-time data ingestion pipelines. In this role, you will be responsible for the reliable flow of streaming ...

SAIC

Data Ops Engineer

San Diego, CA · On-site

$200K - $240K/yr

Description We are seeking a Data Ops Engineer to design, build, and maintain real-time data ingestion pipelines. In this role, you will be responsible for the reliable flow of streaming data from a ...

SAIC

Data Ops Engineer

San Diego, CA · On-site

$200K - $240K/yr

ORA_ON_SITE Description We are seeking a Data Ops Engineer to design, build, and maintain real-time data ingestion pipelines. In this role, you will be responsible for the reliable flow of streaming ...

Xenith Solutions

Data Ops Engineer

San Diego, CA · On-site

$121K - $146K/yr

They are seeking a Data Ops Engineer to design, build, and maintain real-time data ingestion pipelines, ensuring reliable data flow and quality while collaborating with various engineering teams.

Xenith Solutions LLC

Data Ops Engineer

San Diego, CA · On-site

$121K - $146K/yr

We are seeking a Data Operations Engineer to design, build, and maintain real-time data ingestion pipelines. In this role, you will be responsible for the reliable flow of streaming data from a wide ...

Xenith Solutions

Data Ops Engineer

San Diego, CA · On-site

$121K - $145K/yr

We are seeking a Data Operations Engineer to design, build, and maintain real-time data ingestion pipelines. In this role, you will be responsible for the reliable flow of streaming data from a wide ...

Rivian

Staff Software Engineer, Data Ops

Palo Alto, CA · On-site

$206K - $258K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Role Summary The Autonomy org at Rivian is seeking a Staff Software Engineer, Data Ops to join the Data team who can provide expertise in cloud and data engineering and collaborate with technical and ...

Rivian

Staff Software Engineer, Data Ops

Palo Alto, CA · On-site

$206K - $258K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Role Summary The Autonomy org at Rivian is seeking a Staff Software Engineer, Data Ops to join the Data team who can provide expertise in cloud and data engineering and collaborate with technical and ...

Rivian

Staff Software Engineer, Data Ops

Palo Alto, CA · On-site

$206K - $258K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Role Summary The Autonomy org at Rivian is seeking a Staff Software Engineer, Data Ops to join the Data team who can provide expertise in cloud and data engineering and collaborate with technical and ...

Lorven Technologies

ML Ops Engineer

Concord, CA · On-site

Familiarity with data engineering tools (e.g., Airflow, Spark) and ML Ops frameworks. Solid understanding of software engineering principles and DevOps practices. Ability to communicate complex ...

Chai Discovery, Inc

Data Ops

San Francisco, CA · On-site

AI is reinventing life sciences the same way it reinvented software engineering, and Chai is at the ... Data is vital to training frontier AI models, testing research hypotheses, and supporting our ...

Sieve

Product & Ops Lead

San Francisco, CA · On-site

... engineering and data ops • Drive renewals and upsells by identifying new dataset needs and partnership opportunities within existing accounts • Collaborate closely with the partnerships ...

CIM Group, LP

Sr. Machine Learning Ops Engineer

Los Angeles, CA · On-site

$112K - $154K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

The Senior ML Ops Engineer leads the design and maintenance of scalable, secure infrastructure for ... This role collaborates closely with Data Science, Platform Engineering, Information Architecture ...

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Showing results 1-20

All JobsData Ops Engineer JobsData Ops Engineer Jobs in California

Data Ops Engineer information

See California salary details

$43.9K

$128K

$175.2K

How much do data ops engineer jobs pay per year?

As of Aug 16, 2026, the average yearly pay for data ops engineer in California is $128,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,000.00 and $135,700.00 per year, depending on experience, location, and employer.

What is a Data Ops Engineer?

Data Ops Engineers are professionals who bridge the gap between data engineering and operations. They focus on automating, monitoring, and optimizing data pipelines to ensure reliable, efficient, and secure data flow within organizations. Their responsibilities often include managing data integration, workflow orchestration, deployment of data infrastructure, and implementing best practices for data quality and governance. Data Ops Engineers work closely with data scientists, analysts, and IT teams to support data-driven decision-making and maintain high data availability. Their role is crucial in modern organizations that rely on large-scale data processing and analytics.

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

To thrive as a Data Ops Engineer, you need a solid background in data engineering, automation, and cloud infrastructure, often supported by a degree in computer science or related field. Experience with tools like Apache Airflow, Docker, Kubernetes, CI/CD pipelines, and proficiency in scripting languages such as Python or Bash is typically required. Strong problem-solving skills, attention to detail, and effective communication help you collaborate with data teams and troubleshoot complex data workflows. These skills ensure reliable data delivery, streamlined operations, and scalable solutions that support organizational data goals.

What is the difference between Data Ops Engineer vs Data Engineer?

AspectData Ops EngineerData Engineer
CredentialsCertifications in data management, cloud platforms, scriptingCertifications in data engineering, SQL, cloud services
Work EnvironmentFocus on data pipelines, automation, deployment, and monitoringFocus on data modeling, ETL processes, database design
Industry UsageUsed in organizations emphasizing data operations, automation, and DevOps practicesUsed in data-centric roles focusing on building data infrastructure

While both roles work with data infrastructure, Data Ops Engineers primarily focus on automating and managing data pipelines and deployment processes, whereas Data Engineers concentrate on designing and building data systems. The roles often overlap but differ in their core focus areas and responsibilities.

How does a Data Ops Engineer typically collaborate with data scientists and software engineers within an organization?

Data Ops Engineers play a crucial role in bridging the gap between data science and engineering teams. They ensure smooth data pipeline operations, help automate workflows, and support data scientists by providing reliable, scalable infrastructure. Collaboration often involves participating in cross-functional meetings to understand data requirements, troubleshooting data quality issues, and implementing solutions that enable efficient experimentation and model deployment. This collaborative environment helps facilitate quick iterations and reliable delivery of data products.

What are popular job titles related to Data Ops Engineer jobs in California?

For Data Ops Engineer jobs in California, the most frequently searched job titles are:

What job categories do people searching Data Ops Engineer jobs in California look for?

The top searched job categories for Data Ops Engineer jobs in California are:

What cities in California are hiring for Data Ops Engineer jobs?

Cities in California with the most Data Ops Engineer job openings:

Data Ops Engineer jobs near you
Infographic showing various Data Ops Engineer job openings in California as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 12% Part Time, 2% Temporary, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $128,018 per year, or $61.5 per hour.

Data Ops Engineer

SAIC

San Diego, CA • On-site, Remote

$200K - $240K/yr

Full-time

Re-posted 9 days ago

SAIC rating

7.9

Company rating: 7.9 out of 10

Based on 79 frontline employees who took The Breakroom Quiz

79th of 224 rated it services

Job description

Job ID: 2612348

Location: San Diego, CA, US

Date Posted: 2026-07-28

Category: Engineering and Sciences

Subcategory: Systems Engineer

Schedule: Full-Time

Shift: Day Job

Travel: Yes - 10% of the time

Minimum Clearance Required: TS.SCI

Clearance Level Must Be Able to Obtain: None

Potential for Remote Work: ORA_ON_SITE


Description

We are seeking a Data Ops Engineer to design, build, and maintain real-time data ingestion pipelines. In this role, you will be responsible for the reliable flow of streaming data from a wide range of sources into our data platform, ensuring data quality, observability, and scalability. You'll partner closely with data engineers, platform engineers, and analytics teams to deliver trustworthy, low-latency data that supports operational decisions.  This position is on-site in San Diego, CA. Aid the team in delivering continual data feeds to users and monitoring the status of the health of data quality and overall data ingest.

  • Aid the team in delivering continual data feeds to users and monitoring the status of the health of data quality and overall data ingest.
  • Build resilient pipelines with appropriate backpressure, prioritization, retries, and error-handling strategies.
  • Employ a variety of data manipulation and visualization tools to effectively convey status and historical trends to leadership, users, and data team.
  • Collaborate with platform, software, and other data engineers to (re)configure data ingestion pipelines to be more reliable.
  • Work with data in a variety of formats including Excel, CSV, JSON, and XML.
  • Support the incident management process to ensure that incidents are documented and resolved quickly.  Perform root cause analysis to understand and
  • prevent repeated occurrences of data outages.
  • Develop and maintain software to automate monitoring of real-time feeds and alert for timeliness, volume, lineage, and distribution data issues.  Process learnings and rely on historical data from data pipelines, translating them into actionable steps to improve data ingest.
  • Partner with security and governance teams to enforce encryption, authentication authorization, and data classification. 
  • Demonstrate proficiency with frequent-used scripting language (Python, bash) commonly used in data science applications and data analytics.
     

Qualifications

  • U.S. citizenship and an active TS/SCI
  • Bachelor of Science required in the following preferred fields: Computer Science, Mathematics, EE, Physics, Information Systems, or Information Technology.
  • 3+ years of experience in data engineering, data operations, or DevOps roles supporting production data pipelines.
    Tools
  • Apps/Platforms: NiFi, Kafka, Grafana, Prometheus, Apache Flink/Spark Streaming, Snowflake, Elasticsearch, Kafka, MQTT, JMS
    Operating Systems: Windows, Linux (RedHat).

Target salary range: $200,001 - $240,000. The estimate displayed represents the typical salary range for this position based on experience and other factors.

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