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Remote Data Quality Reviewer Jobs in Oregon (NOW HIRING)

Tebra

Data Engineer

OR · On-site +1

$114K - $137K/yr

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

Deckers

Director, Data Governance

OR · On-site +1

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 ...

360training

Data Architect Manager

This is a remote position and we are looking to hire in the following states: AZ, FL, GA, NJ, PA ... Provide technical leadership by making architectural decisions, mentoring engineers, reviewing ...

ConnectWise

IT Enterprise Data Architect

OR · On-site +1

Partners closely with Data Engineering and Information Security teams to ensure data quality ... Onsite, Hybrid, or Remote depending on location. * Occasional travel may be required to support ...

Amerilife Group, LLC

Senior Data Architect

OR · On-site +1

$67.25 - $90/hr

Lead architecture reviews, solution design sessions, and technical governance across enterprise ... Data Quality * Performance Optimization Leadership Competencies * Enterprise architecture ...

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 ...

Amerilife Group, LLC

Senior Data Engineer

OR · On-site +1

$142K - $160K/yr

Data Quality & Governance * Implement enterprise data quality validations. * Develop metadata ... Participate in architecture reviews and code reviews. * Mentor junior engineers. * Drive ...

Deckers

Data Architecture Lead

OR · On-site +1

United States (Remote) Interested applicants must reside in one of the following approved states ... Participate in architecture and design reviews, providing guidance, feedback, and enforcement of ...

Cordance

Data Architect

OR · On-site +1

$63.75 - $82/hr

... quality thresholds, and change management. * Lead technical discovery, architecture reviews, proofs ... Data Governance: Establishes clear ownership, definitions, lineage, quality, security, and ...

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All JobsData Quality Reviewer JobsRemote Data Quality Reviewer JobsRemote Data Quality Reviewer Jobs in Oregon

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 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 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.

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 August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 14% Part Time, 4% Contract, and 1% Nights. Highlights an 90% Physical, 1% Hybrid, and 9% Remote job distribution.

Data Engineer

Tebra

OR • On-site, Remote

$114K - $137K/yr

Full-time

Posted 27 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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