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

Farmers Home Furniture

Sales Person

Louisburg, NC · On-site

Prepares and/or places tags on merchandise; places tags on all merchandise especially for sales ... Requires the ability to review, categorize, prioritize, and/or analyze data. Includes exercising ...

Farmers Home Furniture

Sales Person

Louisburg, NC · On-site

Prepares and/or places tags on merchandise; places tags on all merchandise especially for sales ... Requires the ability to review, categorize, prioritize, and/or analyze data. Includes exercising ...

Farmers Home Furniture

Sales Person

Louisburg, NC · On-site

Prepares and/or places tags on merchandise; places tags on all merchandise especially for sales ... Requires the ability to review, categorize, prioritize, and/or analyze data. Includes exercising ...

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Showing results 41-60

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

Merchandise Data Analyst information

See Raleigh, NC salary details

$33.1K

$80.3K

$132.2K

How much do merchandise data analyst jobs pay per year?

As of Aug 13, 2026, the average yearly pay for merchandise data analyst in Raleigh, NC is $80,333.00, according to ZipRecruiter salary data. Most workers in this role earn between $60,800.00 and $94,300.00 per year, depending on experience, location, and employer.

What is the difference between Merchandise Data Analyst vs Inventory Analyst?

AspectMerchandise Data AnalystInventory Analyst
Required CredentialsBachelor's in Business, Data Analytics, or related field; proficiency in data toolsBachelor's in Supply Chain, Logistics, or related; strong analytical skills
Work EnvironmentRetail or e-commerce companies; data-driven teamsWarehouses, distribution centers, retail stores
Employer & Industry UsageUsed in retail, fashion, and consumer goods industriesCommon in retail, manufacturing, and logistics sectors
Comparison Search IntentAnalyzing sales data, product performance, and trendsManaging stock levels, replenishment, and supply chain efficiency

The Merchandise Data Analyst focuses on analyzing sales and product data to optimize merchandising strategies, while the Inventory Analyst concentrates on managing stock levels and supply chain operations. Both roles require analytical skills and industry knowledge but serve different aspects of retail operations.

What does a merchandise data analyst do?

A Merchandise Data Analyst is responsible for collecting, analyzing, and interpreting data related to merchandise sales, inventory, and customer behavior. They use this information to identify trends, forecast demand, and make recommendations that optimize product assortments and inventory levels. Their insights help retailers improve sales performance, reduce stockouts and overstocks, and enhance customer satisfaction. Merchandise Data Analysts often work closely with buying, marketing, and supply chain teams to support strategic decision-making.

What are the key skills and qualifications needed to thrive as a merchandise data analyst?

To thrive as a Merchandise Data Analyst, you need strong analytical abilities, a solid understanding of retail operations, and proficiency in data analysis, typically supported by a degree in business, mathematics, or a related field. Expertise in tools such as Excel, SQL, Tableau, and experience with merchandising or inventory management systems is highly valuable. Attention to detail, problem-solving skills, and effective communication are critical soft skills for interpreting data and collaborating with cross-functional teams. These skills ensure accurate insights and recommendations that drive inventory optimization, sales growth, and strategic retail decisions.

How does a merchandise data analyst typically collaborate with merchandising and buying teams to influence product assortment decisions?

As a Merchandise Data Analyst, you will work closely with merchandising and buying teams by providing data-driven insights on sales trends, inventory levels, and customer preferences. Your analyses help inform decisions about which products to stock, discontinue, or promote, ensuring that assortments align with market demand and company goals. Regular meetings and cross-functional projects are common, where you'll present findings and recommendations, making your role highly collaborative and influential in shaping the product mix.
What are popular job titles related to Merchandise Data Analyst jobs in Raleigh, NC? For Merchandise Data Analyst jobs in Raleigh, NC, the most frequently searched job titles are:
What job categories do people searching Merchandise Data Analyst jobs in Raleigh, NC look for? The top searched job categories for Merchandise Data Analyst jobs in Raleigh, NC are:
What cities near Raleigh, NC are hiring for Merchandise Data Analyst jobs? Cities near Raleigh, NC with the most Merchandise Data Analyst job openings:
Merchandise Data Analyst jobs near you
Infographic showing various Merchandise Data Analyst job openings in Raleigh, NC as of August 2026, with employment types broken down into 89% Full Time, and 11% Part Time. Highlights an 89% In-person, and 11% Remote job distribution, with an average salary of $80,333 per year, or $38.6 per hour.

Blue Yonder PMM Consultant

Neshent Technologies

Wilders Grove, NC • On-site

Full-time

Posted 5 days ago

Job description

Job Summary

We are seeking an experienced Blue Yonder PMM Consultant with strong expertise in Blue Yonder/JDA Product Management & Merchandising (PMM) solutions. The ideal candidate will have experience developing retail merchandising applications, building data integrations, and supporting enterprise retail processes. This role requires hands-on experience with Blue Yonder technologies, integration frameworks, and modern data pipeline tools.

Required Experience
  • 7+ years of overall IT experience.
  • Hands-on experience with Blue Yonder/JDA PMM or retail merchandising solutions.
Required Skills
  • Strong experience with Blue Yonder/JDA PMM and merchandising systems.
  • Hands-on expertise in BYC Connect, Apache Airflow, and Apache Kafka for data integration and streaming.
  • Proficiency in Java, PL/SQL (packages, stored procedures, functions), and REST APIs.
  • Experience with Control-M for batch job scheduling and workflow automation.
  • Strong understanding of retail merchandising concepts, including:
    • Product Lifecycle Management
    • Assortment Management
    • Product Data Management
    • Inventory Management
    • Order Processing
  • Experience with the Blue Yonder Luminate and Planning suite.
  • Exposure to cloud platforms such as Azure, AWS, or GCP.
  • Familiarity with Agile/Scrum development methodologies.
  • Strong analytical, debugging, and problem-solving skills.
  • Excellent communication and stakeholder management abilities.
Key Responsibilities
  • Design, develop, and support Blue Yonder PMM solutions for retail merchandising and product lifecycle management.
  • Configure and customize PMM modules, including merchandising, product lifecycle, product hierarchy, inventory management, and order processing.
  • Build and maintain data integration pipelines using BYC Connect, Apache Airflow, and Kafka.
  • Develop and support REST APIs and interfaces between Blue Yonder, ERP, and other enterprise applications.
  • Perform data modeling, configuration, testing, deployment, and production support.
  • Translate business and functional requirements into scalable technical solutions.
  • Troubleshoot application, integration, and performance issues while ensuring system stability.
  • Collaborate with cross-functional teams to deliver high-quality retail technology solutions.
  • Participate in system enhancements, upgrades, and implementation projects.
  • Create technical documentation and support knowledge transfer activities.
Preferred Qualifications
  • Bachelor's degree in Computer Science, Information Technology, or a related field.
  • Experience with enterprise retail, merchandising, or supply chain solutions.
  • Knowledge of CI/CD practices and cloud-native application development is a plus.

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