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Remote Data Quality Reviewer Jobs in Hawaii (NOW HIRING)

None Potential for Remote Work: ORA_ON_SITE Description We are seeking a Data Operations Engineer ... Aid the team in delivering continual data feeds to users and monitoring the health of data quality ...

Remote micro1 is engaging Pharmacovigilance Experts to contribute their advanced drug safety ... authoring and reviewing complex safety reports, passionate about data quality, and committed to ...

Remote micro1 is engaging Pharmacovigilance Experts to contribute their advanced drug safety ... authoring and reviewing complex safety reports, passionate about data quality, and committed to ...

Remote micro1 is engaging Microbiologists to contribute their scientific expertise to a unique ... Utilize rubrics and established evaluation criteria to assess data quality and support AI training ...

Your work will shape how models learn, reason, and perform through high-quality, real-world input ... data aligns with industry standards. * Develop and review problem sets, case studies, or scenarios ...

Remote (US, Canada, UK focused) micro1 is engaging Physics Experts (Postdoc / Junior professor) to ... Your work will shape how models learn, reason, and perform through high-quality, real-world input.

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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 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 Hawaii?

For Remote Data Quality Reviewer jobs in Hawaii, the most frequently searched job titles are:

What job categories do people searching Remote Data Quality Reviewer jobs in Hawaii look for?

The top searched job categories for Remote Data Quality Reviewer jobs in Hawaii are:

What cities in Hawaii are hiring for Remote Data Quality Reviewer jobs?

Cities in Hawaii with the most Remote Data Quality Reviewer job openings:

Infographic showing various Remote Data Quality Reviewer job openings in Hawaii 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 Operations Engineer Principal

SAIC

Honolulu, HI • On-site, Remote

$120K - $160K/yr

Full-time

Posted 11 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: 2615413

Location: Honolulu, HI, US

Date Posted: 2026-08-11

Category: Information Technology

Subcategory: Big Data 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 Operations Engineer to design, build, and maintain real-time and near-realtime data ingestion pipelines supporting a mission-critical system and moves data across security domains using cross domain solutions (CDS) / guards. 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, analytics teams, and security/governance personnel to deliver trustworthy, low-latency data that supports operational decisions — while ensuring compliance with cross-domain and data classification requirements. This position is on-site in Honolulu, HI.

Key Responsibilities

  • Aid the team in delivering continual data feeds to users and monitoring the health of data quality and overall data ingest.
  • Design, build, and maintain resilient real-time/near-realtime ingestion pipelines using Apache NiFi and REST APIs, with appropriate backpressure, prioritization, retries, and error-handling strategies.
  • Configure and monitor data flows moving across security domains via cross domain guards/solutions, ensuring data integrity and compliance with transfer policies.
  • Parse, transform, validate, and route structured and unstructured data in a variety of formats, including Excel, CSV, JSON, and XML.
  • Employ data manipulation and visualization tools (e.g., Grafana, Prometheus) to effectively convey pipeline status, data quality, and historical trends to leadership, users, and the data team.
  • Collaborate with platform, software, and other data engineers to (re)configure and continuously improve data ingestion pipeline reliability.
  • Develop and maintain software/scripts to automate monitoring of real-time feeds and alert on timeliness, volume, lineage, and distribution data issues.
  • Translate learnings from historical pipeline data into actionable steps to improve data ingest reliability and performance.
  • Partner with security and governance teams to enforce encryption, authentication, authorization, and data classification requirements across pipelines and cross-domain transfers.
  • Write and maintain scripts (Python, Bash, or similar) to automate data processing, validation, and monitoring tasks.
  • Document data flows, system configurations, and standard operating procedures.

Qualifications

  • TYPICAL EDUCATION AND EXPERIENCE: Bachelors and nine (9) years or more experience; Masters and seven (7) years or more experience ; PhD or JD and four (4) years or more experience.
  • U.S. Citizenship and an active TS/SCI clearance.
  • Bachelor of Science degree in Computer Science, Mathematics, Electrical Engineering, Physics, Information Systems, Information Technology, or related field.
  • 3+ years of experience in data engineering, data operations, or DevOps roles supporting production data pipelines.
  • Proficiency in Python, Bash, or similar scripting languages commonly used in data science/data analytics applications.
  • Working knowledge of the Linux (RedHat) command line; familiarity with Windows environments.
  • Solid understanding of data engineering fundamentals: data pipelines, streaming architectures, ETL/ELT concepts, and data quality principles.
  • Familiarity with JSON, XML, CSV, and Excel data formats, parsing, and transformation.

Preferred Qualifications (Nice to Have)

  • Experience with streaming/messaging platforms and tools: Kafka, JMS, Apache Flink/Spark Streaming.
  • Experience with monitoring/observability tools: Grafana, Prometheus, Elasticsearch.
  • Experience with data platforms such as Snowflake.
  • Familiarity with cross domain solutions/guards (e.g., data diode concepts, transfer validation, content filtering).
  • Experience enforcing encryption, authentication/authorization, and data classification policies in partnership with security/governance teams.
  • Experience with version control tools (e.g., Git) and Agile/Scrum practices.
  • Prior experience in a government, defense, or intelligence community environment.

Target salary range: $120,001 - $160,000. The estimate displayed represents the typical salary range for this position based on experience and other factors.

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