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Remote Data Quality Reviewer Jobs in Oregon (NOW HIRING)

Tebra

Data Engineer

OR · Remote

$114K - $137K/yr

Monitor production data pipelines, identify data quality issues or pipeline failures, and implement ... Remote

Deckers

Director, Data Governance

OR · Remote

United States (Remote) Interested applicants must reside in one of the following approved states ... You'll develop, implement, and oversee enterprise-wide data governance, data quality, and data ...

YipitData

Data Classification Associate, Corporate

OR · On-site +1

$16 - $20.75/hr

... quality assurance processes that catch error patterns that LLMs and manual review miss ... If the remote work is performed outside of these offices, income may be subject to New York State ...

Under Armour, Inc.

Sr. Data Steward

OR · On-site +1

$75K - $100K/yr

Ensure data quality issues are addressed reliably and in a timely fashion. * Gather, understand ... REMOTE #HYBRID Relocation * No relocation provided Base Compensation $75,000.00-$100,000.00 USD ...

360training

Data Architect Manager

This is a remote position and we are looking to hire in the following states: AZ, FL, GA, NJ, PA ... Strong SQL skills and the ability to design, review, debug, and optimize data pipelines, models ...

Wellbe Senior Medical

Data Systems Analyst

$90K - $120K/yr

... quality, and risk adjustment data, alongside internal systems such as EMR , CRM, HR etc. to ... Work Environment Remote Travel may be required up to 15% locally or nationally Pay Transparency $90 ...

NewRocket

AI Data Intelligence Lead

OR · Remote

Remote (Occasional travel as needed) Reports to: Global AI Center of Excellence Lead Why Us ... Anomaly detection and data quality monitoring * Achema mapping and data harmonization across ...

Media.Monks

$130K/yr

Code reviews and pull request workflows * Modular, reusable, and testable code * CI/CD pipelines ... Automated testing (unit, integration, and data quality tests) * Infrastructure as Code

Monks

Code reviews and pull request workflows * Modular, reusable, and testable code * CI/CD pipelines ... Automated testing (unit, integration, and data quality tests) * Infrastructure as Code

YipitData

Senior Data Product Analyst

OR · On-site +1

Product New York, NY (Remote-Friendly) About the Role YipitData is making one of its most ambitious ... Serve as the final reviewer for methodology-related changes that impact product behavior. Product ...

Upstart

Data Analyst, Home Lending HMDA

OR · On-site +1

... quality control testing, and timely regulatory submissions. How you'll make an impact ... Manage HMDA and CRA data integrity reviews, including routine monitoring, exception tracking, and ...

LMI

Data Engineer (Vantage) - Clearance Required

$101K - $174K/yr

Open to Remote. Local preferred at client site in Crystal City VA or Aberdeen MD. LMI is a new ... Data Hygiene: Assist with the cleanup of legacy data models and implement automated data quality ...

LMI

Data Engineer (Vantage) - Clearance Required

$101K - $174K/yr

Open to Remote. Local preferred at client site in Crystal City VA or Aberdeen MD. LMI is a new ... Data Hygiene: Assist with the cleanup of legacy data models and implement automated data quality ...

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Remote Data Quality Reviewer information

What is a Remote Data Quality Reviewer?

A Remote Data Quality Reviewer is a professional who evaluates and ensures the accuracy, completeness, and reliability of data collected or processed by an organization, all while working from a remote location. Their duties often include checking data for errors, inconsistencies, or missing information, and recommending corrections or improvements. They may work with various types of data, such as customer records, survey responses, or financial information, depending on the industry. This role is crucial for maintaining high data standards and supporting decision-making processes within a company.

What does a data quality reviewer do?

A data quality reviewer evaluates datasets to ensure accuracy, completeness, and consistency by identifying and correcting errors. They often use data management tools and follow established standards to maintain high data integrity, supporting reliable decision-making within organizations.

What are some common challenges faced by Remote Data Quality Reviewers, and how can they be addressed?

Remote Data Quality Reviewers often encounter challenges such as managing large data sets, maintaining focus during repetitive review tasks, and ensuring effective communication with distributed teams. Staying organized with clear workflow tools and setting regular check-ins with team members can help mitigate feelings of isolation and prevent errors. Additionally, leveraging automated validation tools and maintaining up-to-date documentation ensures consistency and accuracy in data review processes.

How to make $1000 a week remote?

A Remote Data Quality Reviewer can earn $1000 or more weekly by working full-time hours, often 40 hours per week, and gaining experience or certifications in data management and quality assurance. Increasing income may involve taking on multiple clients, working for companies with higher pay rates, or developing specialized skills in data tools and validation processes.

How can I make 2000 a week working from home?

A Remote Data Quality Reviewer can potentially earn $2,000 per week by working full-time hours, often requiring strong attention to detail, data management skills, and familiarity with data validation tools. Increasing earnings may involve taking on multiple clients, gaining certifications, or working overtime, depending on the employer's pay structure and workload. Consistent high performance and efficiency are key to reaching this income level in remote data review roles.

How to identify fake data entry jobs?

To identify fake data entry jobs, verify the company's legitimacy through official websites and reviews, and be cautious of jobs that require upfront payments or promise unusually high pay for minimal work. Legitimate data entry roles typically do not ask for sensitive personal information early in the application process and provide clear job descriptions and contact details. Using reputable job boards and avoiding offers that seem too good to be true can help prevent scams.

What are the key skills and qualifications needed to thrive as a Remote Data Quality Reviewer, and why are they important?

To thrive as a Remote Data Quality Reviewer, you generally need strong analytical abilities, attention to detail, and experience with data validation, often supported by a bachelor's degree in a relevant field such as statistics, computer science, or information management. Familiarity with data management tools, spreadsheet software (like Excel), and database systems, as well as knowledge of quality assurance frameworks, is typically required. Excellent written communication, critical thinking, and the ability to work independently are important soft skills for this remote position. These capabilities ensure accurate data assessment, help maintain data integrity, and contribute to reliable decision-making across organizations.
What are popular job titles related to Remote Data Quality Reviewer jobs in Oregon? For Remote Data Quality Reviewer jobs in Oregon, the most frequently searched job titles are:
What job categories do people searching Remote Data Quality Reviewer jobs in Oregon look for? The top searched job categories for Remote Data Quality Reviewer jobs in Oregon are:
What cities in Oregon are hiring for Remote Data Quality Reviewer jobs? Cities in Oregon with the most Remote Data Quality Reviewer job openings:
Remote Data Quality Reviewer jobs near you
Infographic showing various Remote Data Quality Reviewer job openings in Oregon as of July 2026, with employment types broken down into 75% Full Time, 2% Part Time, 5% Temporary, and 18% Contract. Highlights an 100% Remote job distribution.

Data Engineer

Tebra

OR • Remote

$114K - $137K/yr

Other

Posted 5 days ago

Job description

About the Role

As a Data Engineer focused on AI/ML, you'll build, maintain, and optimize the data infrastructure that powers Tebra's intelligent features. You'll partner closely with Machine Learning Engineers, Data Scientists, and Software Engineers to transform complex healthcare data into high-quality datasets and real-time features that enable machine learning models.

This is a hands-on engineering role where you'll contribute to scalable data pipelines, improve data quality, and help ensure our AI systems are powered by reliable, performant, and well-governed data. You'll work on modern data platforms and gain experience building solutions that support both model training and production inference.

Your Area of Focus
  • Design, build, and maintain scalable data pipelines for feature extraction, training data generation, and model monitoring.
  • Develop and enhance data systems that support analytics and machine learning workloads, including data lakehouse and feature store technologies.
  • Monitor production data pipelines, identify data quality issues or pipeline failures, and implement improvements to ensure reliability and freshness.
  • Participate in engineering design discussions and contribute to technical decisions around data architecture and pipeline implementation.
  • Build reusable data engineering components, including automated data quality checks, schema validation, and testing frameworks.
  • Translate business requirements into scalable data solutions that enable analytics and machine learning use cases.
  • Optimize SQL queries, Spark workloads, and data processing pipelines to improve performance and scalability.
  • Collaborate with ML Engineers and cross-functional partners to support MLOps best practices, including data versioning, lineage, and reproducibility.
  • Break down technical work into manageable tasks and deliver high-quality solutions within an agile team.
Your Professional Qualifications
  • 3+ years of professional experience in Data Engineering, Software Engineering, or a related field.
  • 2+ years of hands-on experience building and maintaining production data pipelines supporting analytics, reporting, or machine learning workloads.
  • Strong proficiency in Python and SQL with experience developing production-quality data pipelines.
  • Experience with modern data processing technologies such as Spark, Airflow, Kafka, or similar distributed data platforms.
  • Experience working with cloud-based data platforms such as Databricks, Snowflake, Delta Lake, or equivalent lakehouse technologies.
  • Understanding of data modeling, data warehousing, and data governance best practices.
  • Familiarity with machine learning data workflows, including training datasets, feature engineering, and data quality concepts.
  • Experience deploying and supporting production data pipelines with monitoring, testing, and CI/CD practices.
  • Strong problem-solving skills, attention to detail, and the ability to collaborate effectively across engineering and product teams.
  • Excellent communication skills and a desire to continuously learn new technologies and engineering practices.

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