Data Architect

ROLE: Data Architect – Semantic Layer & Reusable Data Products 

Location: Remote 


We are seeking a highly skilled data architect to design and implement standardized data models across diverse source systems and map them to a semantic layer that powers scalable, reusable data products.  This role is central to our strategy of enabling interoperable, interchangeable data integration for downstream analytics, applications, and client-facing products. 
Key Responsibilities 
        · Develop and maintain canonical/standard data models across structured, semi-structured, and unstructured sources 
        
        · Define common entities, relationships, and attributes to support cross-domain integration 
        
        · Map source data to semantic concepts and business definitions to create a unified, business-friendly data layer 
        
        · Collaborate with product, engineering, and analytics teams to ensure models support user-driven exploration and self-service 
        
        · Build and automate modular, reusable data products derived from standard models to integrate data from any source with plug-and-play compatibility for downstream processes 
        
        · Implement versioning, lineage, and change-management practices to ensure consistent consumption 
        
        · Partner with data engineering to design ingestion and transformation patternsthat support interchangeable data flows 
        
        · Enforce modeling standards to ensure new sources can be onboarded with minimal friction 
        
        · Define and maintain metadata, data dictionaries, and modeling guidelines
        
        · Ensure compliance with enterprise governance, data privacy, and security standards 
        
Required Experience :

        · 5+ years of hands-on data modeling or data architecture experience in a cloud-native environment 
        
        · Strong understanding of semantic modeling, data warehouse design, and domain-driven design 
        
        · Proficiency with modeling tools (e.g., Erwin, PowerDesigner, dbt, Collibra, AtScale, LookML) and data platforms like Snowflake and Microsoft Fabric 
        
        · Strong knowledge of SQL and ETL/ELT patterns, APIs, parameter and variable acceptable tools, and event-driven data flows 
        
        · Exceptional ability to translate business concepts into technical models
        
        · Strong communication and collaborationskills to work across engineering, analytics, and business stakeholders 
        
Preferred Experience 
        · Experience implementing federated data platforms or data mesh architectures 
        
        · Familiarity with knowledge graphs, ontologies, and AI-driven semantic enrichment 
        
        · Background in finance, fintech, or other complex multi-source data environments