Senior Data Architect

BeautyHealth•Reston, VA

About The Position

The Senior Data Architect is the enterprise owner of data architecture across the organization’s analytics and data platform ecosystem. This role defines and governs scalable, consistent, and future-ready data architecture standards that enable reliable reporting, self-service analytics, and advanced data-driven decision-making across global business functions. The role ensures data is structured, integrated, and governed in a way that supports both operational systems and analytical workloads, while meeting enterprise requirements for scalability, security, performance, and long-term platform evolution.

Requirements

Bachelor’s degree in Computer Science, Information Systems, Engineering, or related field
7+ years of experience in data architecture, data engineering, or enterprise data platform roles
Strong experience designing enterprise-scale data platforms and analytics architectures
Deep expertise in data modeling (conceptual, logical, dimensional)
Hands-on experience with cloud data platforms (Snowflake strongly preferred; AWS/Azure/GCP acceptable)
Strong understanding of modern data transformation tools (dbt or equivalent)
Experience designing data integration patterns across multiple enterprise systems
Strong understanding of data warehousing principles and analytics architectures
Experience working with BI semantic layers (e.g., Power BI datasets or similar concepts)
Strong knowledge of data governance, metadata, and data lineage principles
Enterprise systems thinking and architectural foresight
Strong abstraction skills and ability to design at conceptual and logical levels
Ability to influence technical direction without direct authority
Strong communication skills across technical and business stakeholders
Structured thinking, documentation discipline, and governance mindset
Ability to balance long-term architecture with practical delivery constraints

Nice To Haves

Master’s degree preferred
Experience architecting modern cloud data stacks (Snowflake + dbt + BI ecosystem)
Exposure to enterprise ERP/CRM systems (SAP, Oracle, Salesforce, NetSuite, etc.)
Experience in global or multi-entity enterprise environments
Familiarity with DevOps concepts applied to data platforms
Architecture certifications (TOGAF or equivalent) preferred but not required
Experience supporting AI/ML or advanced analytics platforms is a plus

Responsibilities

Define and maintain the enterprise data architecture blueprint across operational and analytical domains, ensuring alignment between business strategy, data capabilities, and technology platforms, and establishing the long-term structural design of the organization’s data ecosystem.
Establish and govern architecture standards for modern data platforms, including Snowflake, dbt, and associated integration layers, ensuring consistency in how data is ingested, transformed, stored, and consumed across the enterprise.
Design scalable, reusable architecture patterns that support analytics, reporting, and BI consumption, ensuring data structures are optimized for performance, maintainability, and enterprise-wide reuse.
Lead the development of the enterprise data platform roadmap, translating business growth, modernization initiatives, and emerging analytics requirements into a coherent architectural evolution strategy.
Define enterprise-wide conceptual, logical, and dimensional data models across key business domains, ensuring consistency in how data entities, relationships, and metrics are structured and interpreted across systems.
Establish canonical definitions for critical business entities and metrics, ensuring a single source of truth for reporting, analytics, and decision-making across all functional areas.
Design and standardize dimensional modeling approaches, including facts, dimensions, and data marts, ensuring scalable, high-performance structures that support both operational reporting and advanced analytics use cases.
Define integration architecture patterns across ERP, CRM, SaaS, APIs, and internal applications, ensuring data is reliably and securely ingested, transformed, and made available across operational and analytical environments.
Architect batch and near-real-time data ingestion frameworks, ensuring data flows are resilient, scalable, and aligned with enterprise requirements for latency, reliability, and governance.
Define best practices for transformation architecture within Snowflake and dbt, including modular design, ELT patterns, lineage management, and cloud-native processing standards that ensure maintainability and extensibility.
Establish architectural standards for BI semantic layers, ensuring alignment between enterprise data models and BI consumption layers such as Power BI datasets, while standardizing metric definitions, calculation logic, and reusable business rules.
Own enterprise data governance architecture, including metadata management, data lineage, quality frameworks, and compliance alignment, while ensuring systems meet security, privacy, and regulatory requirements such as SOX where applicable.
Provide architectural leadership across data engineering, BI, and business systems teams, including design reviews, technical guidance, and mentorship, while ensuring adherence to enterprise standards and long-term platform strategy.
Develop and maintain enterprise architecture documentation, reference models, and standardized design patterns, and lead architecture review processes for all major data initiatives to ensure consistency, scalability, and alignment with enterprise principles.
Additional duties as assigned.