Director, Engineering - Data, Analytics and Reporting

BRAND DESCRIPTION: 

At Five Below our growth is a result of the people who embrace our purpose: We know life is way better when you are free to Let Go & Have Fun in an amazing experience, filled with unlimited possibilities, priced so low, you can always say yes to the newest, coolest stuff! Just ask any of our over 20,000 associates who work at Five Below and they’ll tell you there’s no other place like it. It all starts with our purpose and then, The Five Below Way, which is our values and behaviors that each and every associate believes in. 

It’s all about culture at Five Below, making this a place that can inspire you as much as you inspire us with big ideas, super energy, passion, and the ability to make the workplace a WOWplace! 

POSITION SUMMARY: 

The Director of Data, Analytics & Reporting leads the enterprise strategy, governance, and delivery of data, analytics, and reporting capabilities across the retail organization. This role owns key data platforms—including Master Data Management (MDM), the Enterprise Data Platform (EDP), and Customer Data Platform (CDP)—and ensures the business has trusted, integrated, and actionable insights across merchandising, supply chain, stores, e-commerce, finance, and customer engagement. 

This leader drives advanced analytics, enterprise reporting, master data quality, and data platform modernization while managing resources, evaluating solutions, and developing capabilities across the data organization. The Director partners with business and technology leaders to enable data-driven decisions that improve sales performance, operational efficiency, inventory flow, and customer loyalty, and supports AI-driven initiatives in collaboration with the AI Engineering team. 

Key Responsibilities 

1. Enterprise Data Strategy & Governance (Retail-Focused) 

• Own enterprise master data domains including product, customer, store, vendor, supply chain, and item attributes. 

• Lead Master Data Management (MDM) initiatives to ensure clean, consistent, governed data across all merchandising, supply chain, store, and digital systems. 

• Oversee Customer Data Platform (CDP) strategy to unify customer identities and support loyalty, personalization, and omnichannel marketing. 

• Define data governance models, KPIs, standards, and quality frameworks aligned with retail operations and enterprise analytics needs. 

• Partner with Enterprise Architecture to ensure scalable, modern data platform design and alignment with EDP, MDM, and CDP strategies. 

2. Retail Analytics, Insights & Advanced Modeling 

• Deliver analytics for store performance, category productivity, supply chain health, inventory planning, promotions, and customer behavior. 

• Integrate MDM and CDP data to enable segmentation, customer 360, pricing decisions, assortment optimization, and personalized engagement. 

• Build predictive and prescriptive analytics models for demand forecasting, replenishment, logistics optimization, labor planning, and promotional effectiveness. 

• Translate insights into actionable recommendations for Merchandising, Store Operations, Supply Chain, Marketing, and Executive Leadership. 

3. Enterprise Reporting, Dashboards & Self-Service Analytics 

• Lead enterprise reporting strategy, dashboard design, KPI frameworks, and self-service enablement across stores, regions, supply chain, digital, and customer domains. 

• Ensure reporting accuracy through alignment with master data hierarchies (SKU, category, store cluster, customer segment). 

• Drive standardization, automation, and adoption of BI tools such as Power BI, Tableau, and Looker. 

• Institute robust data quality and validation processes to ensure reporting is reliable, timely, and trusted. 

4. Platform Leadership – MDM, EDP & CDP 

• Oversee roadmap, health, and evolution of the enterprise data platform (EDP), MDM, and CDP capabilities. 

• Ensure creation of high-quality golden records and integrated data pipelines supporting analytics, AI, operations, and enterprise reporting. 

• Evaluate and select data, analytics, and reporting solutions—balancing cost, scalability, capability, and architectural standards. 

• Manage build-vs-buy decisions and lead solution assessments to ensure long-term sustainability and alignment with business outcomes. 

• Partner with CRM, Merchandising, Supply Chain, Digital, and Store Operations to embed governed, high-quality data into operational workflows. 

5. Leadership, Resource Management & Stakeholder Engagement 

• Lead teams of BI engineers, data analysts, data product managers, and MDM/CDP specialists. 

• Manage resource planning, workload distribution, staffing models, and capability development across all data functions. 

• Forecast team capacity across enterprise initiatives and ensure alignment with program and platform priorities. 

• Manage vendor partners, contractors, and consulting engagements to ensure delivery quality and cost-effective execution. 

• Build a culture of data literacy, continuous improvement, and high accountability in data delivery. 

• Communicate complex analytical and technical concepts clearly to business and executive stakeholders. 

Qualifications Required 

• Bachelor’s or master's in data science, Statistics, Computer Science, Business Analytics, or related fields. 

• 10+ years in data analytics, BI, or enterprise reporting, with 5+ years in leadership roles (preferably in retail or consumer-facing industries). 

• Strong expertise in data platforms, enterprise reporting solutions, BI tools (SQL, Python, Power BI, Tableau), and analytics delivery. 

• Hands-on experience with MDM, EDP, and/or CDP platforms. 

• Demonstrated success in managing teams, resource planning, capability development, and vendor management. 

• Proven ability to assess, select, and implement enterprise data and analytics solutions. 

Qualifications Preferred 

• Experience driving customer 360, loyalty analytics, or digital personalization programs. 

• Knowledge of retail data governance frameworks, enterprise architecture, and data quality models. 

• Experience building team capability frameworks, operating models, or resource management structures for data organizations. 

• Exposure to AI/ML enablement and modern cloud data architectures. 

Success Criteria 

• Accurate, consistent master data across products, stores, suppliers, and customers. 

• Trusted enterprise reporting widely used by executives, merchants, supply chain, store leaders, and marketing teams. 

• Measurable lift in sales performance, inventory optimization, logistics efficiency, and customer engagement from insights. 

• Scalable, modern data platforms (MDM, EDP, CDP) enabling analytics, AI models, and operational decision-making. 

• Well-managed resource capacity, strong delivery execution, and high-performing teams