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Remote Data Engineering Jobs in California (NOW HIRING)

SAIC

Data Ops Engineer

San Diego, CA · On-site +1

$200K - $240K/yr

Engineering and Sciences Subcategory: Systems Engineer Schedule: Full-Time Shift: Day Job Travel ... None Potential for Remote Work: ORA_ON_SITE Description We are seeking a Data Ops Engineer to ...

10a Labs

Data Engineer, Web Scraping

San Francisco, CA · Remote

$125K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Our adversarial red teaming, model evaluations, and intelligence collection enable engineering ... Fully remote, U.S.-based * Health Benefits: Comprehensive health, dental, and vision coverage

Robert Half

Data Engineer III

San Ramon, CA · On-site +1

$128K - $153K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Align data engineering solutions with business strategy, including support for Agentic AI workloads Data Infrastructure & Platform * Own health, scalability, and modernization of data infrastructure ...

Robert Half

Data Engineer III

San Ramon, CA · On-site +1

$128K - $153K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Align data engineering solutions with business strategy, including support for Agentic AI workloads Data Infrastructure & Platform * Own health, scalability, and modernization of data infrastructure ...

Sequoia Connect

Junior Data Engineer

Mountain View, CA · On-site +1

Familiarity with PySpark, AWS managed services, data engineering best practices, and code ... Remote If you meet these qualifications and are pursuing new challenges, start your application on ...

The Rockridge Group

Data Engineer

Emeryville, CA · Remote

$132K - $159K/yr

TITLE: DATA ENGINEER LOCATION: 100% remote Skillsets/experience: * Engineer background * Google Applications/Analytics experience required * Google Search console experience required * Google Tag ...

Horizontal Talent

Sr. Data Engineer

San Francisco, CA · On-site +1

$60 - $96/hr

  • Medical

  • Dental

  • Vision

  • Retirement

Join a dynamic data engineering team supporting large-scale analytics and cloud data solutions for a hybrid onsite role in San Francisco, CA. This position focuses on building reliable, high ...

Vibrant Planet

Data Engineer

Truckee, CA · Remote

$200K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

You will work across the engineering organization, partnering with scientists, analysts, and ... This is a remote role, so working comfortably and effectively in a distributed team is crucial. KEY ...

Discord

Data Engineer

San Francisco, CA · Remote

$180K - $200K/yr

Partner closely with data science, product manager, and engineering teams to translate business questions into well modeled, performant, and discoverable data assets * Establish and enforce data ...

Meta

Data Engineer, Product Analytics

Sunnyvale, CA · On-site +1

$147K/yr

Data Engineering: You will guide teams by building optimal data artifacts (including datasets and visualizations) to address key questions. You will refine our systems, design logging solutions, and ...

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Remote Data Engineering information

How do remote data engineers typically collaborate with other team members across different time zones?

Remote data engineers often work with distributed teams, which requires strong communication and organization skills. They collaborate using tools like Slack, Zoom, and project management platforms to stay aligned on data pipeline development, troubleshooting, and deployment. Regular stand-ups, asynchronous documentation, and clear communication of progress are essential for ensuring everyone is on the same page, regardless of location. Flexibility in working hours and proactive scheduling of meetings help facilitate effective collaboration and project delivery.

What is remote data engineering?

Remote data engineering involves designing, building, and maintaining data systems and pipelines while working from a location outside of a traditional office. Remote data engineers use tools to collect, process, and store large sets of data, making it accessible for analysis and business decision-making. They collaborate with teams virtually, often using cloud-based technologies, to ensure that data infrastructure is reliable, scalable, and secure. This role requires strong technical skills in programming, databases, and data architecture, as well as the ability to communicate effectively in a distributed work environment.

What are the key skills and qualifications needed to thrive as a remote data engineer?

To thrive as a Remote Data Engineer, you need strong programming skills (such as Python, Java, or Scala), experience with data modeling, ETL processes, and a solid understanding of database systems, often supported by a degree in computer science or a related field. Proficiency with big data tools like Apache Spark, Hadoop, cloud platforms (AWS, Azure, GCP), and certifications in these technologies is highly valued. Excellent problem-solving abilities, self-motivation, and clear communication are crucial soft skills for remote collaboration and project delivery. These competencies ensure effective data pipeline development, reliable data management, and seamless teamwork across distributed environments.

Can you work remotely as a data engineer?

Yes, remote data engineering roles are common, allowing professionals to work from various locations. These jobs often require strong skills in SQL, cloud platforms, and data pipeline tools, and may involve collaboration through online communication tools.

What is the difference between Remote Data Engineering vs Remote Data Analyst?

AspectRemote Data EngineeringRemote Data Analyst
Required CredentialsBachelor's in CS, Data Science, or related field; experience with SQL, Python, cloud platformsBachelor's in Statistics, Data Science, or related; proficiency in Excel, SQL, visualization tools
Work EnvironmentBuilds data pipelines, manages databases, works with cloud infrastructureAnalyzes data sets, creates reports, visualizes data insights
Employer & Industry UsageTech companies, finance, healthcare, e-commerceMarketing agencies, finance, retail, consulting

Remote Data Engineering focuses on designing and maintaining data infrastructure, while Remote Data Analysts interpret data to provide insights. Both roles require strong analytical skills but differ in technical depth and responsibilities.

What are the most commonly searched types of Data Engineering jobs in California?

The most popular types of Data Engineering jobs in California are:

What are popular job titles related to Remote Data Engineering jobs in California?

For Remote Data Engineering jobs in California, the most frequently searched job titles are:

What job categories do people searching Remote Data Engineering jobs in California look for?

The top searched job categories for Remote Data Engineering jobs in California are:

What cities in California are hiring for Remote Data Engineering jobs?

Cities in California with the most Remote Data Engineering job openings:

Remote Data Engineering jobs near you
Infographic showing various Remote Data Engineering job openings in California as of August 2026, with employment types broken down into 80% Full Time, and 20% Part Time. Highlights an 100% Remote job distribution.

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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