Principal Data Architect

Principal Data Architect (Hands-On) 

Department: Technology & Data 

Location: Remote (East or Central time zones preferred) 

Type: Full-Time 

About the Role 

David's Bridal is seeking an experienced Principal Data Architect to lead the design, modernization, and long-term strategy of our enterprise data ecosystem. This role defines and establishes a unified “One David’s Bridal” data architecture enterprise data domains, reusable data assets, and a clear multi-year roadmap enabling consistent, AI-ready data across every channel and function. The role is both strategic and hands-on: ideal for someone who can architect large-scale solutions while actively contributing to modeling, integrations, and implementation. 

You will be accountable for creating a cohesive enterprise data architecture that spans David’s Bridal’s full business landscape, including: 

• eCommerce and digital experience (Shopify) 

• Retail stores, appointments, and in-store selling 

• Merchandising, planning, and inventory 

• Supply chain, order management, and fulfillment 

• Marketing, CRM, and customer analytics 

• Finance, operations, and corporate functions 

This role works deeply across business and technology to understand domain-level data structures, flows, and usage, and synthesize them into a single, integrated enterprise architecture view. A core focus is to identify, standardize, and drive adoption of reusable data assets and enterprise definitions, ensuring the organization benefits from shared, consistent, high-quality data across use cases, platforms, and business lines. 

You will define both the target-state architecture and the practical transformation journey, evolving today’s fragmented data landscape into a well-structured, scalable, AI-ready ecosystem built on a unified Snowflake and SQL Server environment. Success is measured by clarity and adoption of the enterprise data architecture, reuse of data assets across domains, and enablement of scalable data, analytics, and AI platforms. 

What You Would Be Responsible For 

Enterprise Data Architecture Vision & “One David’s Bridal” Blueprint 

• Define, own, and maintain the enterprise data architecture vision, target state, and roadmap, ensuring scalability, maintainability, and alignment with business strategy 

• Develop a unified “One David’s Bridal” data architecture blueprint integrating all business domains, cross-functional data flows, and platform-aligned data structures 

• Create clear architectural representations that simplify the enterprise data landscape for technical and executive audiences 

Deep Business Domain Alignment 

• Partner closely across eCommerce, stores, merchandising and planning, supply chain and fulfillment, marketing, finance, and operations 

• Build deep understanding of business processes, domain data models, and data usage and dependencies — including order lifecycle, OMS, payments, fulfillment, customer segmentation, and attribution 

• Translate domain complexity into standardized enterprise data models and structures 

Enterprise Data Domains & Modeling 

• Define and standardize enterprise data domains and sub-domains, domain ownership boundaries, and conceptual and logical data models 

• Design and implement sophisticated data models supporting commerce, customer lifecycle, finance, supply chain, inventory, and digital transformation initiatives 

• Ensure consistency and interoperability across domains, enabling domain-oriented architecture aligned to modern principles (data products and reuse-first design) 

Reusable Data Assets & Enterprise Definitions 

• Lead identification and standardization of reusable data assets across the organization 

• Define and promote enterprise-level data definitions and canonical data structures 

• Drive reuse of core data entities (e.g., customer, product, order, inventory, appointment, store, transaction) and shared datasets and data products 

• Ensure reusable assets are easily discoverable, accessible, and consumable — including governed Power BI semantic models — and drive adoption across the business to maximize enterprise value from shared data 

Data Governance, Classification & Transparency 

• Lead standards for data governance, privacy, lineage, cataloging, quality, and master data management 

• Establish a comprehensive view of enterprise data assets: what data exists, where it resides, and how it is used 

• Define consistent frameworks for data asset classification, domain tagging, and business vs. technical metadata 

• Align classification and handling with compliance obligations (SOC2, GDPR, CCPA, PCI-DSS) 

Data Architecture Roadmap & Transformation Journey 

• Define a multi-year data architecture roadmap from current to target state 

• Identify redundant and fragmented data assets, opportunities for consolidation and reuse, and critical architecture gaps 

• Sequence transformation in alignment with business priorities and platform delivery roadmaps, ensuring the architecture is actionable and tied to real execution 

Standards, Patterns & Architectural Guidance 

• Define enterprise standards for data design and modeling, data integration and interoperability, and data product structure 

• Provide architectural oversight for ELT frameworks, automation, and orchestration tooling. 

• Drive best practices for Power BI semantic models, architecture, and performance governance across business functions 

• Establish reusable architecture patterns that enable platform scalability and AI-ready data design 

• Provide clear guidance to engineering and platform teams 

Hands-On Delivery 

• Build and optimize secure data pipelines integrating Shopify and multiple enterprise systems into the unified Snowflake and SQL Server environment 

• Contribute directly to data modeling, integrations, and implementation — not just architecture on paper 

• Optimize large, complex, high-volume SQL workloads for performance and cost 

Enterprise Influence, Alignment & Mentorship 

• Act as the senior technical authority for data architecture across the organization 

• Drive alignment across business and technology stakeholders, promoting a reuse-first, domain-driven data culture 

• Mentor internal data engineering teams and build capability in domain architecture, data modeling, and enterprise data design 

• Influence leadership on data strategy and platform investment decisions 

• Foster deep business engagement, practical execution-oriented architecture, and high-quality, consistent outputs 

Qualifications & Experience 

• 7–10+ years of experience in enterprise data engineering, architecture, or platform ownership roles 

• Proven expertise in Snowflake (design, security, cost management, workload optimization) and SQL Server (schema design, tuning, stored procedures, indexing) 

• Advanced SQL capability with demonstrated experience optimizing large, complex, high-volume workloads 

• Strong experience implementing and supporting Power BI enterprise deployments (governance, semantic layer design, modeling patterns) 

• Hands-on experience with modern ELT tooling and orchestration (dbt, Airflow, Stitch, Databricks, etc.) 

• Demonstrated eCommerce data experience, ideally including Shopify — understanding of order lifecycle, OMS, payments, fulfillment, customer segmentation, and attribution 

• Experience building scalable architecture frameworks aligned to business intelligence, operational reporting, and AI/ML readiness 

• Proven ability to define enterprise-wide architecture frameworks and influence across complex organizations without direct control 

• Strong blend of business domain expertise and technical depth 

Preferred Experience 

• Retail or multi-channel commerce experience (stores + eCommerce) 

• API experience (REST / GraphQL) and complex system integrations 

• Knowledge of compliance and governance: SOC2, GDPR, CCPA, PCI-DSS 

• Python experience for workflow automation or integration scripting 

Who You Are 

• A senior technical leader who is both visionary and execution-minded 

• Able to unify fragmented data landscapes into cohesive, simple architectures 

• Able to influence at the executive level while guiding implementation details 

• Practical and business-oriented — not just an architect on paper 

• Balances strategic clarity with execution realism, and communicates the big picture clearly 

• Thrives in transforming legacy data landscapes into modern, scalable platforms