Senior Data Platform Architect – Snowflake Lakehouse Leader

CGS Business Solutions; Irvine (CA); On-site; USD 150,000 - 180,000; Full time

Job summary

CGS Business Solutions is seeking a Principal Data Platform Architect to define and execute the enterprise data platform strategy for a nationwide manufacturing client. The role centers on a Snowflake-based lakehouse, scalable self-service BI, and governance to support AI initiatives.

You will drive standards for data quality, metadata, and integration while partnering with data science and engineering teams to enable ML/AI capabilities across the enterprise.

Qualifications

• Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or a related field.
• Master’s degree preferred.
• 10+ years in data architecture, data engineering, or enterprise data platforms.
• Experience designing cloud-based data platforms, preferably Snowflake.
• Hands-on with ELT/ETL, data modeling, and metadata management (dbt, Fivetran).
• Strong experience in enterprise integration using API-led, event-driven, and batch patterns.
• Proven ability to lead architecture strategy and governance.

Responsibilities

• Define and lead the Enterprise Data Platform Strategy and Roadmap.
• Design and Govern Snowflake-based lakehouse architecture across layers.
• Lead integration architecture across systems and data domains.
• Enable and expand self-service BI and analytics with governed semantic layers.
• Establish foundation for ML/AI platforms and ML Ops practices.

Skills

Data architecture

Leadership

Snowflake

ETL/ELT

Data modeling

API integration

Self-service BI

MLOps

Cloud platforms

Education

Bachelor's degree

Master's degree preferred

Tools

dbt

Fivetran

Job description

CGS Business Solutions is seeking a Principal Data Platform Architect to define and execute the enterprise data platform strategy for a nationwide manufacturing client. The role centers on a Snowflake-based lakehouse, scalable self-service BI, and governance to support AI initiatives.

You will drive standards for data quality, metadata, and integration while partnering with data science and engineering teams to enable ML/AI capabilities across the enterprise.