Principal Architect - Enterprise Data Engineering

Mattel•El Segundo, CA

3d•$168,000 - $195,000•Onsite

About The Position

We are looking for an experienced Principal Architect with deep expertise in Cloud Data Engineering and Google Cloud Platform (GCP). This role will drive end-to-end data architecture, enabling scalable, secure, and AI-ready data platforms that support advanced analytics and business decision-making.

Requirements

Strong experience in Cloud Data Engineering
Hands-on expertise in ERP integrations, including Big Query, Pub/Sub, Cloud Storage, Composer (Airflow), CA Scheduler
Finance (GL, AP, AR)
Procurement and Purchase Orders
Inventory and Supply Chain
Customer and Vendor Master Data
Collaborate with business teams to translate ERP functional requirements into scalable data models and pipeline
Proficiency in SQL and Python
Experience with ETL/ELT, data modeling, and performance optimization
Knowledge of batch & streaming architectures and API integrations
Bachelor’s or Master’s degree in Computer Science, Engineering, or related field
10+ years of experience in Data Engineering, ETL, and Data Architecture
Proven experience in designing and implementing enterprise data solutions
Strong expertise in: Google Cloud Platform (BigQuery, GCS, Pub/Sub, Cloud Functions)
Apache Airflow (workflow orchestration)
SQL and data modeling (dimensional modeling, ELT patterns)
Strong hands-on experience with ERP integrations (SAP, Oracle ERP, finance and supply chain systems)
Demonstrated a growth mindset by staying curious and continuously learning, embracing challenges, and improving themselves.

Responsibilities

Own and lead end-to-end solution architecture for data and analytics platforms
Design scalable, high-performance data solutions using Oracle and GCP services
Define data architecture standards, best practices, and governance frameworks
Build and optimize ETL/ELT pipelines for batch and real-time processing
Architect and implement end-to-end O2C, R2P, R2R, P2R integration solutions for systems such as SAP, Oracle ERP, Coupa, and Anaplan
Collaborate with business stakeholders to translate requirements into technical solutions
Drive cloud transformation and modernization initiatives
Ensure data quality, security, compliance, and cost optimization
Incorporate AI/ML capabilities to enable predictive and intelligent analytics
Apply data mesh and domain-driven design principles to enable decentralized, scalable data ownership
Provide technical leadership and mentorship to engineering teams