Sr Data Architect

Five Below•Philadelphia, PA

About The Position

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 27,000 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!

Requirements

12+ years of experience in data architecture and enterprise data modeling.
Strong experience with: Conceptual, logical, and physical data modeling, Erwin data Modeling, Dimensional modeling (Databricks), Enterprise canonical data models.
Hands-on experience with Erwin Data Modeler or similar modeling tools.
Experience designing data for modern Lakehouse or Data Warehouse platforms.
Solid SQL skills and comfort partnering with data engineers.
Strong communication skills and a collaborative mindset.

Nice To Haves

Experience in retail, consumer, or multi-domain enterprises.
Hands-on exposure to Databricks and the broader Azure ecosystem (e.g., Delta Lake, Spark SQL, ADLS Gen2, Azure Data Factory, Synapse, Purview).
Experience supporting Customer 360, enterprise analytics, or supply chain data.
Familiarity with BI tools and semantic modeling (e.g., Power BI).

Responsibilities

Design Data That Makes Sense: Understand how data flows across our retail business — from stores and supply chain to customers and finance. Define enterprise data architecture that supports analytics, reporting, and operational use cases. Design data models for key domains like Customer, Product, Sales, Store, Supplier, and Supply Chain.
Be the Go-To Expert for Data Modeling: Lead conceptual, logical, and physical data modeling using Erwin Data Modeler or similar tools. Apply best practice modeling approaches: Data Vault 2.0 for scalable, auditable enterprise data, Dimensional (Star / Snowflake) models for reporting and analytics. Create and maintain enterprise canonical models so teams are speaking the same “data language.” Set and maintain modeling standards — naming, keys, definitions, and documentation — so data stays clean and consistent. Leverage AI-assisted data architecture and modeling capabilities in Erwin and associated tools (e.g., Quest DMI/DM) to accelerate model development, improve consistency, and support impact analysis.
Support Our Lakehouse Platform: Design schemas and data structures optimized for Databricks, Delta Lake, and Spark SQL. Architect and model the data layer for Azure based collaborative ecosystem (Ex: SQL, PostgreSQL and MySQL). Partner with data engineering teams to align data models with ingestion pipelines and transformations. Ensure data is easy to consume for dashboards, reports, semantic layers, APIs, and downstream systems.
Build Trust Through Governance & Quality: Design data with governance in mind — lineage, auditability, and ownership built in from the start. Partner with security and governance teams to support PII/PCI-safe data designs and enterprise policies. Help define data quality expectations so teams can trust the numbers they see. Create clear documentation and architecture artifacts that teams can actually use.
Collaborate Across the Business: Translate business needs into practical, scalable data designs. Be a trusted partner for Product, Engineering, BI, and Analytics teams. Participate in Agile delivery, providing architecture guidance and design reviews. Explain complex data concepts in a clear, approachable way — no jargon needed.