Analyst, Merch Dt Anlyts & Eng

Overall Job Summary

The Data Analytics & Engineering Analyst is responsible for leveraging data analytics and engineering tools to develop, optimize, and deliver actionable insights that drive business decisions across the Merchandising function. This role involves building, maintaining, and enhancing data models, pipelines, and analytical frameworks to support complex business problems. Key responsibilities include designing scalable data solutions, performing predictive and explanatory analyses, and ensuring data integrity to optimize merchandising strategies, maximize sales, and improve margins.

Essential Duties and Responsibilities (Min 5%)

• Key Areas of Focus: Leverage data engineering and analytics to drive Pricing Optimization, Localization & Space Optimization, and Profit Improvement, ensuring strategic merchandising decisions that maximize sales, margins, and operational efficiency.
• Develop and Maintain Data Infrastructure: Become a functional expert in merchandising business data by defining data elements, shaping data structures, and optimizing data pipelines to ensure accuracy, efficiency, and scalability for analytics and reporting.
• Build & Enhance Data Visualization Solutions: Design, develop, and maintain interactive dashboards and reports using tools like Power BI or Tableau, providing real-time insights into merchandising trends, category performance, and sales patterns.
• Optimize Merchandising Data Pipelines: Engineer and automate data extraction, transformation, and loading (ETL) processes to streamline reporting and analytics across merchandising activities, including promotional impact analysis and space optimization.
• Analyze & Identify Key Business Insights: Work cross-functionally with stakeholders to understand data needs, provide data-driven recommendations, and develop analytical solutions that enhance decision-making in merchandising strategies.
• Support Senior Leadership with Data-Driven Decisions: Develop and present detailed merchandising insights, including category analysis, product placement strategies, private brand performance, and promotional activity impact.
• Develop & Implement Predictive Models: Support Data Science team with machine learning, data mining, and statistical techniques to build models that optimize retails and space utilization, enhance customer shopping experience, and improve product adjacencies.
• Drive Business Solutions Through Data Engineering & Advanced Analytics: Extract and interpret complex data from structured and unstructured sources to uncover insights that drive improvements in merchandising layout, space productivity, and customer convenience.
   

Required Qualifications

Experience: 2-3 years of experience in Retail Analytics, Merchandising Analytics, Pricing, Finance, or a related business field, with a strong focus on data-driven decision-making and performance optimization.
Experience working with large datasets, relational databases, and data visualization to support strategic initiatives in pricing, space optimization, localization, and profitability analysis.  Prior experience in data engineering, ETL processes, and automation.

Education: Bachelor’s degree in Business, Statistics, Finance, Data Science, Economics, or a related field from an accredited college or university.  MBA or advanced degree in Mathematics, Statistics, Operations Research, Business, Marketing, Economics, Data Science, or an equivalent field is preferred but not required.  Any suitable combination of education and experience will be considered.

Professional Certifications: Certifications in SQL, Data Analytics, Data Engineering, or Business Intelligence tools are a plus.  SQL, Python, R, Alteryx, Power BI, Tableau, AWS, or Azure certifications preferred.
 

Preferred knowledge, skills or abilities

• Intermediate to expert-level SQL proficiency, with experience in complex query writing, optimization, and relational database management.
• Expertise in data visualization tools such as Power BI, Tableau, or equivalent.
• Experience with Alteryx, Python, R, or other data analytics and automation tools is a plus.
• Strong background in handling large datasets and database management to support business insights.
• Data engineering experience (e.g., building and maintaining ETL pipelines, data modeling) is preferred.
• Proficiency in Microsoft Office Suite, with advanced Excel skills for financial and data analysis.
• Strong problem-solving, analytical thinking, and strategic mindset to drive data-backed decision-making.
• Excellent communication, presentation, and storytelling skills to convey insights to both technical and non-technical stakeholders.
• Ability to work cross-functionally and collaborate with multiple teams to align analytics with business objectives.
• Retail industry experience is highly preferred.
• Ability to prioritize tasks under tight deadlines while maintaining a high level of accuracy and attention to detail.
• Fluent in English (spoken and written) with strong documentation and reporting skills.

Working Conditions

Physical Requirements

Disclaimer

This job description represents an overview of the responsibilities for the above referenced position.  It is not intended to represent a comprehensive list of responsibilities.  A team member should perform all duties as assigned by his/ her supervisor.

Company Info

At Tractor Supply and Petsense by Tractor Supply, our Team Members are the heart of our success. Their dedication, passion, and hard work drive everything we do, and we are committed to supporting them with a comprehensive and accessible total reward package. We understand the evolving needs of our Team Members and their families, and we strive to offer meaningful, competitive, and sustainable benefits that support their well-being today and in the future.
Our benefits extend beyond medical, dental, and vision coverage, including company-paid life and disability insurance, paid parental leave, tuition reimbursement, and family planning resources such as adoption and surrogacy assistance, for eligible Team Members. While all Team Members have access to a broad range of rewards, eligibility and specific offerings may vary depending on the role, individual plan requirements and eligibility criteria.