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Data Reviewer Jobs in Raleigh, NC (NOW HIRING)

Senior Data Architect

Raleigh, NC · On-site

$65.25 - $87.50/hr

Reviewing Snowflake query performance * Optimizing warehouse utilization and workload management ... Reducing data movement and duplication * Enhancing pipeline scalability and resiliency * Ensuring ...

Reviews information for Uniform Education Reporting System (UERS) reporting areas. * Maintains data storage of student records for up to 5 years. * Provides information and/or training to school ...

Reviews information for Uniform Education Reporting System (UERS) reporting areas. Maintains data storage of student records for up to 5 years. Provides information and/or training to school staff on ...

Master Data Specialist

Raleigh, NC

$16.50 - $22/hr

Review and verify customer documentation in accordance with company policies and compliance guidelines. Submit and track customer master data requests through the MDG system and follow up on pending ...

New

Data Entry Clerk

Creedmoor, NC · On-site

$23 - $26/hr

Review and verify certificates to ensure data integrity and compliance. * Utilize Excel and Microsoft Office Suite for data management and reporting. * Perform clerical duties and order entry tasks ...

Data Engineer

Chapel Hill, NC · On-site

$115K - $145K/yr

Data Engineer Reporting To: Manager, Data Engineering Location: Chapel Hill, NC; Minneapolis, MN ... Achieve operational excellence in software development by participating in and leading code reviews ...

Write and review portions of detailed specifications for the development of system components of ... Mentor lead data engineers interested in consultancy on development methodologies and optimization ...

Consulting Data Engineer

Raleigh, NC · On-site

$104K - $174K/yr

Write and review portions of detailed specifications for the development of system components of ... Mentor lead data engineers interested in consultancy on development methodologies and optimization ...

Consulting Data Engineer

Raleigh, NC · On-site

$104K - $174K/yr

Write and review portions of detailed specifications for the development of system components of ... Mentor lead data engineers interested in consultancy on development methodologies and optimization ...

Consulting Data Engineer

Raleigh, NC · On-site

$104K - $174K/yr

Write and review portions of detailed specifications for the development of system components of ... Mentor lead data engineers interested in consultancy on development methodologies and optimization ...

Write and review portions of detailed specifications for the development of system components of ... Mentor lead data engineers interested in consultancy on development methodologies and optimization ...

Consulting Data Engineer

Raleigh, NC · On-site

$104K - $174K/yr

Write and review portions of detailed specifications for the development of system components of ... Mentor lead data engineers interested in consultancy on development methodologies and optimization ...

Vice President, Data Science

Raleigh, NC · On-site

$177K - $350K/yr

Acts as a technical mentor to other data scientists through review, pairing, and example, limited people management whereappropriate. Compensation/Benefits Information: (This section is only ...

Vice President, Data Science

Raleigh, NC · On-site

$177K - $350K/yr

Acts as a technical mentor to other data scientists through review, pairing, and example, limited people management whereappropriate. Compensation/Benefits Information: (This section is only ...

Showing results 21-40

Data Reviewer information

See Raleigh, NC salary details

$12

$25

$42

How much do data reviewer jobs pay per hour?

As of Aug 15, 2026, the average hourly pay for data reviewer in Raleigh, NC is $25.48, according to ZipRecruiter salary data. Most workers in this role earn between $13.99 and $35.24 per hour, depending on experience, location, and employer.

What is the difference between Data Reviewer vs Data Analyst?

AspectData ReviewerData Analyst
Required CredentialsTypically a bachelor's degree in data management, IT, or related fields; certifications like CDMP are commonBachelor's degree in statistics, data science, or related fields; certifications like CAP or Microsoft certifications are common
Work EnvironmentMostly office-based, working with data validation tools and softwareOffice or remote, analyzing data sets, creating reports, and visualizations
Employer & Industry UsageUsed in industries like finance, healthcare, and government for data quality assuranceUsed across industries for data-driven decision making and reporting

While both roles involve working with data, Data Reviewers focus on validating and ensuring data accuracy, whereas Data Analysts interpret data to generate insights. Understanding these differences helps in choosing the right career path or job search focus.

What is a data reviewer?

A data reviewer helps an organization review and interpret data for accuracy and interpretation. Data reviewers are necessary for many fields, including software development, quality assurance, medical and health care professions, and accounting, to name a few. Your responsibilities and duties are to look through collected data that has been entered into a spreadsheet or other database. You check it for any errors and manage issues you find. Some data reviewer positions, such as in medical research, include an analytical component; you help the research team to glean insight from the collected data.

What are the key skills and qualifications needed to thrive as a data reviewer, and why are they important?

To thrive as a Data Reviewer, you need strong analytical skills, attention to detail, and typically a background in life sciences, statistics, or a related field. Familiarity with data management systems, electronic data capture (EDC) platforms, and compliance standards such as GCP is commonly required. Excellent problem-solving, critical thinking, and communication skills help you identify discrepancies and collaborate with cross-functional teams. These competencies are crucial for ensuring data integrity, regulatory compliance, and the reliability of research outcomes.

How does a data reviewer typically collaborate with other teams to ensure data quality?

Data Reviewers work closely with data entry specialists, analysts, and project managers to verify the accuracy and consistency of datasets. They often participate in cross-functional meetings to discuss data discrepancies and establish best practices for data validation. This collaboration helps maintain high-quality data standards and ensures that any issues are promptly identified and resolved, supporting the overall goals of the organization.

What cities near Raleigh, NC are hiring for Data Reviewer jobs?

Cities near Raleigh, NC with the most Data Reviewer job openings:

Infographic showing various Data Reviewer job openings in Raleigh, NC as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 14% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $53,001 per year, or $25.5 per hour.

Senior Data Architect

First Citizens Bank

Raleigh, NC • On-site

$65.25 - $87.50/hr

Full-time

Posted 6 days ago


First Citizens Bank rating

7.4

Company rating: 7.4 out of 10

Based on 106 frontline employees who took The Breakroom Quiz

107th of 171 rated banks


Job description

Overview

The Senior Data Architect is a senior technical leader within Enterprise Data & Analytics (ED&A) responsible for defining, designing, and implementing enterprise-scale data architectures that enable trusted, governed, and business-ready data across the organization.

This role requires deep hands-on expertise across transactional systems (OLTP), analytical platforms (OLAP), modern cloud data platforms, data integration, and enterprise data modeling. The Senior Data Architect is expected to operate from strategy through implementation, partnering with engineering teams to design scalable solutions while actively participating in architecture reviews, complex data modeling, performance optimization, data product design, and platform modernization initiatives.

The ideal candidate brings extensive experience designing and implementing modern data ecosystems leveraging AWS, Snowflake, Data Vault 2.0, DBT, API-based integration patterns, event-driven architectures, metadata management, and AI-ready data foundations.


Responsibilities
Enterprise Data Architecture & Design
  • Define and evolve enterprise data architecture standards, patterns, and reference architectures.
  • Develop target-state architectures supporting ED&A strategic objectives and Nexus platform evolution.
  • Lead architecture design across operational, analytical, reporting, regulatory, and AI use cases.
  • Drive consistency across data acquisition, storage, transformation, governance, and consumption layers.
  • Establish architecture guardrails balancing agility, scalability, maintainability, and regulatory compliance.
Modern Data Platform Architecture

Serve as a senior technical architect responsible for end-to-end design of the Nexus ecosystem including:

Data Ingestion Layer
  • Qlik Replicate and CDC patterns
  • Event-driven ingestion architectures
  • API-driven integrations
  • Batch and near real-time ingestion frameworks
  • External and third-party data integration
Data Storage & Processing Layers
  • AWS S3 data lake architecture
  • Landing and ingestion zones
  • Snowflake data platform architecture
  • Raw Data Vault implementation
  • Business Data Vault design
  • Consumption and semantic layers
  • Data sharing and data product architectures
Transformation & Orchestration
  • DBT architecture and modeling standards
  • ELT pipeline design
  • Reusable transformation frameworks
  • Astronomer (Airflow) orchestration patterns
  • Workflow dependency management
  • Data observability and monitoring
Operational Analytics
  • API-enabled data products
  • Fargate-based services
  • Near real-time analytics solutions
  • Event streaming architectures
  • Operational reporting architectures
Enterprise Data Modeling Leadership

Provide deep expertise across multiple modeling disciplines:

OLTP Modeling
  • Third Normal Form (3NF)
  • Operational application schemas
  • Transaction processing systems
  • Customer, account, loan, and transaction data structures
  • Source system integration patterns
Analytical Modeling (OLAP)
  • Star schemas
  • Snowflake schemas
  • Fact and dimension design
  • Aggregate layer strategies
  • Semantic modeling
Data Vault 2.0
  • Hubs
  • Links
  • Satellites
  • Business Vault design
  • Point-in-time structures
  • Bridge tables
  • Auditability and lineage patterns
Information Architecture
  • Enterprise canonical models
  • Business capability mapping
  • Customer 360 architectures
  • Reference and master data design
  • Domain-driven architecture
  • Architects in this role are expected to actively review and contribute to data models rather than simply approve designs.
Data Products & Domain Architecture
  • Drive adoption of data product thinking across ED&A.
  • Define standards for ownership, accountability, quality, discoverability, and reuse.
  • Partner with business domains to establish trusted and reusable analytical assets.
  • Design scalable domain-oriented architectures supporting Data Mesh principles where appropriate.
  • Enable self-service consumption through governed data products.
Data Governance by Design

Partner closely with Governance teams to embed controls directly within architectural designs.

Responsibilities include:

  • Metadata architecture
  • Business glossary alignment
  • Technical and business lineage
  • Data quality architecture
  • Data contract implementation
  • Sensitive data classification
  • Policy-based access control
  • Data retention and auditability
  • Leverage Collibra, BigID, and platform-native capabilities to improve trust and transparency across enterprise data assets.
Performance Optimization & Engineering Excellence

Actively troubleshoot and improve platform performance by:

  • Reviewing Snowflake query performance
  • Optimizing warehouse utilization and workload management
  • Designing scalable partitioning and clustering strategies
  • Improving ELT processing efficiency
  • Reducing data movement and duplication
  • Enhancing pipeline scalability and resiliency
  • Ensuring efficient storage and compute utilization
  • Expected to participate in technical deep-dives and solution reviews with engineering teams.
AI & Advanced Analytics Architecture
  • Define architectural foundations for enterprise AI initiatives.
  • Design AI-ready data products and curated consumption layers.
  • Support feature engineering and model-serving architectures.
  • Enable trusted, explainable, and governed AI data pipelines.
  • Partner with Data Science teams to ensure scalability of predictive and generative AI solutions.
  • Architect retrieval, metadata, and knowledge-layer capabilities supporting future GenAI initiatives.
Technical Leadership
  • Lead architecture reviews across strategic initiatives and programs.
  • Influence technical direction across engineering, analytics, governance, and business teams.
  • Mentor engineers, architects, and modelers on modern architecture principles.
  • Establish engineering standards, design patterns, and reusable frameworks.
  • Provide thought leadership on emerging technologies and industry best practices.
  • Serve as the escalation point for complex architecture and modeling challenges.

Qualifications

Bachelor's Degree and 6 years of experience in Enterprise data architecture, advanced data solutions, cloud platforms OR High School Diploma or GED and 10 years of experience in Enterprise data architecture, advanced data solutions, cloud platforms

Preferred Qualifications

  • Financial Services or Banking industry experience.
  • Experience modernizing legacy data warehouse environments.
  • Experience architecting large-scale Customer 360 solutions.
  • Experience supporting regulatory and risk reporting ecosystems.
  • Knowledge of Data Mesh and Data Product operating models.
  • TOGAF, CDMP, SnowPro, AWS, or equivalent certifications.
Experience
  • 12+ years of experience in Data Engineering, Data Architecture, Information Management, or Analytics Engineering.
  • 5+ years serving as a lead architect for enterprise-scale data platforms.
  • Proven experience designing and implementing modern cloud data platforms.
  • Demonstrated experience leading large-scale data modernization programs.
  • Experience working directly with engineering teams on implementation, optimization, and troubleshooting.
Modern Data Platforms
  • Snowflake
  • AWS Data Services
  • Amazon S3
  • Data Lake and Lakehouse architectures
  • Cloud-native data ecosystems
Data Engineering
  • ELT/ETL architectures
  • Data integration patterns
  • Change Data Capture (CDC)
  • Event-driven architectures
  • API-based integration
  • Data orchestration frameworks
Nexus Core Technologies
  • Snowflake
  • DBT
  • Qlik Replicate
  • Astronomer / Apache Airflow
  • AWS
  • Data Vault 2.0
  • Collibra
  • BigID
Data Modeling
  • Conceptual, Logical and Physical Data Modeling
  • Data Vault 2.0
  • Dimensional Modeling
  • Canonical Modeling
  • Master Data Management
  • Reference Data Management
Data Management
  • Data Governance
  • Data Quality
  • Data Lineage
  • Metadata Management
  • Data Cataloging
  • Data Contracts

Benefits are an integral part of total rewards and First Citizens Bank is committed to providing a competitive, thoughtfully designed and quality benefits program to meet the needs of our associates. More information can be found at https://jobs.firstcitizens.com/benefits.

Qualifications:

Bachelor's Degree and 6 years of experience in Enterprise data architecture, advanced data solutions, cloud platforms OR High School Diploma or GED and 10 years of experience in Enterprise data architecture, advanced data solutions, cloud platforms

Preferred Qualifications

  • Financial Services or Banking industry experience.
  • Experience modernizing legacy data warehouse environments.
  • Experience architecting large-scale Customer 360 solutions.
  • Experience supporting regulatory and risk reporting ecosystems.
  • Knowledge of Data Mesh and Data Product operating models.
  • TOGAF, CDMP, SnowPro, AWS, or equivalent certifications.
Experience
  • 12+ years of experience in Data Engineering, Data Architecture, Information Management, or Analytics Engineering.
  • 5+ years serving as a lead architect for enterprise-scale data platforms.
  • Proven experience designing and implementing modern cloud data platforms.
  • Demonstrated experience leading large-scale data modernization programs.
  • Experience working directly with engineering teams on implementation, optimization, and troubleshooting.
Modern Data Platforms
  • Snowflake
  • AWS Data Services
  • Amazon S3
  • Data Lake and Lakehouse architectures
  • Cloud-native data ecosystems
Data Engineering
  • ELT/ETL architectures
  • Data integration patterns
  • Change Data Capture (CDC)
  • Event-driven architectures
  • API-based integration
  • Data orchestration frameworks
Nexus Core Technologies
  • Snowflake
  • DBT
  • Qlik Replicate
  • Astronomer / Apache Airflow
  • AWS
  • Data Vault 2.0
  • Collibra
  • BigID
Data Modeling
  • Conceptual, Logical and Physical Data Modeling
  • Data Vault 2.0
  • Dimensional Modeling
  • Canonical Modeling
  • Master Data Management
  • Reference Data Management
Data Management
  • Data Governance
  • Data Quality
  • Data Lineage
  • Metadata Management
  • Data Cataloging
  • Data Contracts

Benefits are an integral part of total rewards and First Citizens Bank is committed to providing a competitive, thoughtfully designed and quality benefits program to meet the needs of our associates. More information can be found at https://jobs.firstcitizens.com/benefits.

Education:UNAVAILABLEEmployment Type: FULL_TIME

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