Sr. Data Engineer Specialist

SAMYANG AMERICA INC•Brea, CA

1d•$80,000 - $95,000

About The Position

Samyang America stands as the #1 Gen Z brand, boldly shaping the future of food culture with innovative flavors, viral trends, and unforgettable brand experiences. We don’t just create food - we craft moments that spark excitement, inspire connection, and celebrate bold individuality. Our mission is to bring daring, delicious products to the market that resonate deeply with the next generation of food lovers. From iconic spicy noodles to creative new launches, we are driven by passion, creativity, and a commitment to pushing the boundaries of taste and culture. At Samyang America, you’ll join a dynamic team that thrives on innovation, collaboration, and a shared love for bold flavor experiences. We value fresh ideas, energetic spirit, and the courage to lead trends rather than follow them. If you’re ready to be part of a brand that’s more than just food - a brand that moves culture and creates unforgettable moments - join our team today! Position Summary: The Data Engineer will be responsible for building and maintaining the data pipelines and infrastructure that power Samyang America’s enterprise data platform. This role focuses on developing reliable, scalable, and efficient data workflows that ingest, transform, and deliver data for analytics, reporting, and AI applications.

Requirements

3–6+ years of experience in data engineering or data pipeline development.
Strong proficiency in SQL and at least one programming language (Python preferred).
Experience building ETL/ELT pipelines and data workflows.
Familiarity with cloud platforms (AWS, Azure, or GCP).

Nice To Haves

Experience with tools such as Airflow, dbt, Spark, or similar.
Experience with modern data platforms (Snowflake, Databricks, etc.).
Exposure to real-time data processing or streaming systems.
Experience working with business data (sales, marketing, finance, etc.).

Responsibilities

Build and maintain ETL/ELT pipelines to ingest data from multiple sources:
ERP, CRM, marketing platforms
Financial systems
External data sources
Ensure pipelines are robust, scalable, and optimized for performance.
Develop processes to clean, standardize, and transform raw data into analysis-ready datasets.
Implement data validation and quality checks to ensure accuracy and consistency.
Optimize data workflows for efficiency and cost.
Support the implementation and operation of the enterprise data lake and analytics platform.
Collaborate with external vendor teams on platform build and enhancements.
Monitor system performance and troubleshoot issues as needed.
Work closely with the Data Architect to implement data models and standards.
Partner with Analytics and AI teams to ensure data is delivered in formats that support business use cases and modeling.
Enable faster access to data for business users and analysts.