Principal Data Architect (Hands-On) Remote (EST/CST preferred)
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