Sr. Data Architect Specialist

SAMYANG AMERICA INC•Brea, CA

13h

About The Position

The Data Architect will play a critical role in designing the structural foundation of Samyang America’s data ecosystem, ensuring that data is organized, governed, and optimized for analytics, AI, and business decision-making. This role focuses on defining data models, standards, and architecture frameworks that enable scalability, consistency, and long-term usability across the enterprise data platform.

Requirements

5+ years of experience in data architecture, data modeling, or database design.
Strong experience with data modeling techniques (star schema, dimensional modeling, etc.).
Familiarity with cloud data platforms (AWS, Azure, or GCP).
Strong understanding of data governance, metadata, and data quality principles.
Proficiency with SQL and data modeling tools.
Structured thinker – brings clarity and order to complex data environments
Systems mindset – designs for scale and long-term usability
Collaborative partner – works effectively with engineering and analytics teams
Detail-oriented – ensures precision in data definitions and models

Nice To Haves

Experience with platforms such as Snowflake, Databricks, or similar.
Experience working with ERP, CRM, or marketing data systems.
Exposure to analytics or AI use cases and how data supports them.

Responsibilities

Design and maintain enterprise data models (conceptual, logical, and physical) aligned to business needs.
Define structures for key domains including: Sales & revenue data, Consumer & marketing data, Product & innovation pipeline, Financial and operational data.
Ensure alignment between business definitions and technical data structures.
Establish and enforce data standards, naming conventions, and taxonomy frameworks.
Define data lineage, ownership, and metadata management practices.
Partner with Data Engineering to ensure governance is embedded in pipelines and systems.
Design how data flows across systems (ERP, CRM, marketing platforms, external data sources).
Define integration patterns to ensure clean, consistent, and unified data assets.
Support the creation of a single source of truth across the organization.
Work closely with Data Engineers to ensure architecture is implemented correctly.
Partner with Analytics and AI teams to ensure data is structured for advanced use cases and modeling.
Translate business requirements into scalable data architecture solutions.