ZipRecruiter

Log In

1

Master Data Analyst Jobs in Raleigh, NC (NOW HIRING)

First Citizens Bank

Senior Data Architect

Raleigh, NC · On-site

$65.25 - $87.50/hr

This role requires deep hands-on expertise across transactional systems (OLTP), analytical ... Reference and master data design * Domain-driven architecture * Architects in this role are ...

First Citizens Bank

Senior Data Architect

Raleigh, NC · On-site

$65.25 - $87.50/hr

This role requires deep hands-on expertise across transactional systems (OLTP), analytical ... Reference and master data design * Domain-driven architecture * Architects in this role are ...

previous page

Showing results 41-60

All JobsMaster Data Analyst JobsMaster Data Analyst Jobs in Raleigh, NC

Master Data Analyst information

See Raleigh, NC salary details

$19

$43

$74

How much do master data analyst jobs pay per hour?

As of Aug 23, 2026, the average hourly pay for master data analyst in Raleigh, NC is $43.11, according to ZipRecruiter salary data. Most workers in this role earn between $29.66 and $53.75 per hour, depending on experience, location, and employer.

What is a master data analyst?

Master Data Analysts are professionals responsible for managing and maintaining an organization's critical business data, often referred to as 'master data.' This includes key information about customers, products, suppliers, and other core business entities. Their work ensures that data is accurate, consistent, and accessible across different departments and systems. Master Data Analysts also help establish data governance standards, support data integration projects, and troubleshoot data quality issues to support business operations and decision-making.

What does a master data analyst do?

A master data analyst monitors and examines master and key data within a company or organization. As a master data analyst, your job duties include developing databases to support business goals, implementing standards for collecting and storing data, and using data to gain key business insights. The career typically requires a bachelor’s degree in IT, data science, or a related field and work experience in data analysis or software programming. Additional qualifications include strong analytical and computer skills, as well as an understanding of database architecture.

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

To thrive as a Master Data Analyst, you need a strong background in data management, analytics, and a relevant degree such as computer science, information systems, or business. Familiarity with data management tools like SAP, Oracle, SQL, and experience with data governance frameworks or related certifications are typically required. Excellent attention to detail, problem-solving abilities, and effective communication skills help distinguish top performers in this role. These competencies are critical for ensuring data accuracy, supporting business decisions, and maintaining consistent data standards across the organization.

How does a master data analyst typically collaborate with other departments to maintain data quality?

A Master Data Analyst regularly works with teams such as IT, finance, supply chain, and operations to ensure data consistency and integrity across systems. This collaboration often involves participating in cross-functional meetings, clarifying data requirements, and resolving discrepancies in master data. Effective communication and problem-solving skills are essential, as the analyst serves as a bridge between technical and business stakeholders to implement data governance policies and improve data processes.

What is the difference between Master Data Analyst vs Data Analyst?

AspectMaster Data AnalystData Analyst
CredentialsBachelor's degree in data-related field; certifications like CDMP or DAMA often preferredBachelor's degree in statistics, mathematics, or related field; certifications are optional
Work EnvironmentFocus on managing and maintaining master data across departmentsAnalyze data sets to generate reports and insights for decision-making
Industry UsageCommon in organizations with complex data management needsWidespread across various industries for data analysis tasks

The main difference is that a Master Data Analyst specializes in managing and maintaining core organizational data, ensuring data quality and consistency. In contrast, a Data Analyst primarily focuses on analyzing data to support business decisions. Both roles require strong analytical skills, but the Master Data Analyst emphasizes data governance and integrity, often working closely with IT and data management teams.

What jobs can I do with a master's in data analytics?

A master's in data analytics qualifies you for roles such as data analyst, data scientist, business intelligence analyst, and data engineer. These positions involve analyzing large datasets, creating reports, and using tools like SQL, Python, or R to support decision-making across various industries.
More about Master Data Analyst jobs

What are popular job titles related to Master Data Analyst jobs in Raleigh, NC?

For Master Data Analyst jobs in Raleigh, NC, the most frequently searched job titles are:

What job categories do people searching Master Data Analyst jobs in Raleigh, NC look for?

The top searched job categories for Master Data Analyst jobs in Raleigh, NC are:

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

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

Master Data Analyst jobs near you
Infographic showing various Master Data Analyst job openings in Raleigh, NC as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $89,671 per year, or $43.1 per hour.

Senior Data Architect

First Citizens Bank

Raleigh, NC • On-site

$65.25 - $87.50/hr

Full-time

Posted 14 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

106th 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

What First Citizens Bank employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Apply