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Remote Data Quality Jobs in Berkeley, CA (NOW HIRING)

talentpluto

Research Engineer

San Francisco, CA · On-site +1

$140K - $250K/yr

Remote Industry: AI training data infrastructure Compensation: $140K-$250K base, plus equity About ... Because data flows through a decentralized marketplace, ensuring quality at scale is the single ...

talentpluto

Research Engineer

San Francisco, CA · Remote

$140K - $250K/yr

Remote Industry: AI training data infrastructure Compensation: $140K-$250K base, plus equity About ... Because data flows through a decentralized marketplace, ensuring quality at scale is the single ...

YO AI Labs

GitHub Contributor - Remote

San Francisco, CA · Remote

$55 - $160/hr

Contract Location: Remote Scope of Work: * Contribute expert-level code samples, debugging ... data quality. * Review and validate peer-contributed code and technical submissions for accuracy ...

Runpod Inc

Senior Data Engineer

San Francisco, CA · On-site +1

$124K - $169K/yr

Data quality is an engineered property of the system, not a dashboard someone checks. As a Senior ... Most roles are remote work first with an inclusive, collaborative teams utilizing slack as the main ...

YO AI Labs

Medical Coder - Remote

San Francisco, CA · Remote

$50 - $80/hr

Remote Job Overview We are seeking experienced Medical Coders to contribute their healthcare coding ... improve AI training data quality. Required Skills * Medical Coding * ICD-10 * CPT * CPC ...

Verse

Software Engineer, Data Engineering

San Francisco, CA · On-site +1

$134K - $162K/yr

United States (remote) What is Verse? The race to AI has become the race to power. Every ... Ensure data quality, contracts and integrity with best practices around access, governance, and ...

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Showing results 21-40

All JobsData Quality JobsRemote Data Quality JobsRemote Data Quality Jobs in Berkeley, CA

Remote Data Quality information

See Berkeley, CA salary details

$20

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$87

How much do remote data quality jobs pay per hour?

As of Sep 8, 2026, the average hourly pay for remote data quality in Berkeley, CA is $50.74, according to ZipRecruiter salary data. Most workers in this role earn between $34.13 and $66.54 per hour, depending on experience, location, and employer.

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

AspectRemote Data QualityRemote Data Analyst
Required CredentialsData quality certifications, SQL, data management skillsData analysis certifications, SQL, statistical skills
Work EnvironmentFocus on data accuracy, validation, and cleansingFocus on data interpretation, reporting, and insights
Employer & Industry UsageUsed in data governance, compliance, and database managementUsed in business intelligence, marketing, and operations

Remote Data Quality specialists primarily focus on ensuring data accuracy, consistency, and integrity within databases, often working on data validation and cleansing. Remote Data Analysts interpret data sets to generate reports and insights for decision-making. While both roles require strong SQL and data management skills, Data Quality roles emphasize data validation processes, whereas Data Analysts focus on analysis and visualization.

What are the most commonly searched types of Data Quality jobs in Berkeley, CA?

The most popular types of Data Quality jobs in Berkeley, CA are:

What cities near Berkeley, CA are hiring for Remote Data Quality jobs?

Cities near Berkeley, CA with the most Remote Data Quality job openings:

Remote Data Quality jobs near you
Infographic showing various Remote Data Quality job openings in Berkeley, CA as of August 2026, with employment types broken down into 68% Full Time, 16% Part Time, and 16% Contract. Highlights an 100% Remote job distribution, with an average salary of $105,532 per year, or $50.7 per hour.

Research Engineer

talentpluto

San Francisco, CA • On-site, Remote

$140K - $250K/yr

Full-time

Re-posted 23 days ago

Job description

Location: Remote (United States)
Work Model: Remote
Industry: AI training data infrastructure
Compensation: $140K-$250K base, plus equity
About the Company
Our partner is a YC-backed company building a new kind of marketplace in the AI training data space. Rather than operating as a labor marketplace, they provide infrastructure that lets data producers transform their existing data into formats AI labs want and sell it directly to those labs. This democratized model unlocks far more high-value data sources, and the team is growing quickly to keep up with demand.
The Opportunity
This is the company's top hiring priority and a genuinely hard research problem. Because data flows through a decentralized marketplace, ensuring quality at scale is the single biggest bottleneck to growth. As a Research Engineer, you will build the automated systems that verify and assure data quality so that suppliers consistently deliver excellent data to buyers.
You will start by digging into the data manually to understand failure modes, then design systems to automate quality checks at scale, combining rule-based approaches with AI for fuzzier cases and human-in-the-loop review where it makes sense. This is fundamentally a research role focused on building automated systems, not manual QA.
Responsibilities
  • Identify data quality issues including inconsistencies, formatting problems, and ingestion challenges
  • Perform initial manual data quality review to deeply understand failure modes
  • Build systems to automate quality checks at scale using rule-based and AI-driven approaches
  • Design hybrid systems that balance automation with human-in-the-loop review where appropriate
  • Continuously improve verification methods as the data landscape and AI tooling evolve
Requirements
  • Deeply technical, with a strong learning slope and the ability to ramp quickly in a fast-moving field
  • Background in AI/ML engineering, or software engineering at an AI-focused company with visible data ingestion and processing experience
  • Ability to reason about likely data quality problems from first principles
  • Comfortable owning ambiguous, open-ended problems end to end
  • Comfortable working in person, full-time, in a San Francisco office
  • Bonus: experience working with noisy or unstructured data, or judgment on when to use automation versus human-in-the-loop review

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