AI Data Architect Remote Role

AI Data Architect

Location: REMOTE

Domain Expertise: Strong preferences for Retail industry background-specifically with store-side operations, point-of-sale (POS), supply chain, or e-commerce workflows. (Candidates with heavy Finance or Healthcare enterprise experience will also be strongly considered).

Required

• Seniority & Experience: 10+ years of progressive experience in data architecture, data engineering, and enterprise database design.
• Core Cloud Platform: Deep expertise in Snowflake architecture, multi-cluster management, performance optimization, and data sharing within complex enterprise environments.
• Cloud Infrastructure: Strong hands-on experience with AWS native data services (e.g., S3, Glue, Redshift, Athena, IAM, EKS/ECS).
• Pipeline Frameworks: Demonstrated experience with enterprise orchestration tools, specifically Astronomer / Apache Airflow.
• Advanced SQL: Exceptional, advanced SQL skills for complex analytics, data transformation, optimization, and query tuning.
• Modern Data Concepts: Proven understanding of semantic layer design (e.g., dbt, Cube, AtScale), data cataloging, and metadata management.

We are seeking a seasoned Data Architect to own and evolve our enterprise data ecosystem. In this high-impact role, you will lead the architecture of our cloud-native data platform, centered around Snowflake and AWS. You will be responsible for designing scalable, high-performance data models, building unified semantic layers, and establishing modern governance frameworks across a complex enterprise landscape.

The ideal candidate is a strategic technical leader with deep experience in retail environments-bridging store operations and e-commerce-who can translate business needs into robust, future-ready data foundation. You will also lay the groundwork for AI/ML capabilities, data catalogs, and graph-based metadata systems while communicating effectively with both executive leadership and hands-on engineering teams.

Key Responsibilities Enterprise Architecture & Snowflake Management

• Lead the architectural design and optimization of our enterprise data platform built on Snowflake and AWS.
• Model complex data flows across a large, distributed organization, ensuring high availability, performance tuning, cost control, and security.
• Define and implement data modeling standards (3NF, Dimensional/Kimball, Data Vault) optimized for large-scale analytical and operational workloads.

Pipeline & Data Flow Design

• Architect reliable, enterprise-grade data pipelines using frameworks such as Astronomer (Apache Airflow) to orchestrate complex ETL/ELT processes.
• Partner with engineering teams to ensure low-latency data integration from diverse source systems, including POS, ERP, CRM, and digital platforms.

Semantic Layers, Cataloging & AI Readiness

• Design and deploy enterprise semantic layers to standardize business metrics and provide a single source of truth across BI and AI applications.
• Implement data cataloging and metadata management solutions to ensure data discoverability, lineage tracking, and governance.
• Prepare our data architecture for next-generation AI/ML integration, incorporating modern semantic structures and maintaining awareness of knowledge graph architectures to support advanced context retrieval..

Required Qualifications & Technical Skills

• Seniority & Experience: 8+ years of progressive experience in data architecture, data engineering, and enterprise database design.
• Core Cloud Platform: Deep expertise in Snowflake architecture, multi-cluster management, performance optimization, and data sharing within complex enterprise environments.
• Cloud Infrastructure: Strong hands-on experience with AWS native data services (e.g., S3, Glue, Redshift, Athena, IAM, EKS/ECS).
• Pipeline Frameworks: Demonstrated experience with enterprise orchestration tools, specifically Astronomer / Apache Airflow.
• Advanced SQL: Exceptional, advanced SQL skills for complex analytics, data transformation, optimization, and query tuning.
• Domain Expertise: Strong preferences for Retail industry background-specifically with store-side operations, point-of-sale (POS), supply chain, or e-commerce workflows. (Candidates with heavy Finance or Healthcare enterprise experience will also be strongly considered).
• Modern Data Concepts: Proven understanding of semantic layer design (e.g., dbt, Cube, AtScale), data cataloging, and metadata management.
• Communication: Outstanding verbal and written communication skills with a track record of driving cross-departmental alignment.