POSTED 7/28/2026
We are seeking a hands-on Lead Data Engineer to join the Data & AI Supply Chain organization and drive the design, development, and delivery of enterprise-scale data products on Google Cloud Platform (GCP). This role will support Supply Chain initiatives across Sourcing, Transportation, and Warehouse Management Systems (WMS) by building scalable cloud-native data solutions that enable advanced analytics and AI-driven decision-making. The ideal candidate will bring deep expertise in modern data engineering, cloud-native architectures, ETL/ELT development, and enterprise data modeling while collaborating with cross-functional business and technology teams.
Design, develop, and implement scalable data pipelines and enterprise data products on Google Cloud Platform (GCP).
Build and optimize cloud-native data solutions using Dataproc, BigQuery, SQL, and dbt.
Design scalable data models supporting analytical and operational reporting requirements.
Develop robust ETL/ELT pipelines to ingest, transform, and publish data from enterprise systems.
Collaborate with Product Managers, Business Analysts, Solution Architects, Data Architects, and business stakeholders to translate business requirements into scalable technical solutions.
Lead technical design discussions and perform code reviews to ensure engineering quality and best practices.
Optimize cloud-based data processing for performance, scalability, reliability, and cost efficiency.
Implement monitoring, testing, and operational best practices for production workloads.
Build reusable frameworks, engineering standards, and technical documentation.
Support production issue resolution and continuous improvement initiatives.
Participate in Agile ceremonies including sprint planning, backlog refinement, and estimation.
Mentor junior engineers and promote engineering best practices.
8+ years of experience in Data Engineering with demonstrated technical leadership.
Strong hands-on experience building enterprise data platforms on Google Cloud Platform (GCP).
Expert-level experience with Dataproc, BigQuery, SQL, and dbt.
Strong understanding of modern ETL/ELT architecture and large-scale data processing.
Experience designing dimensional, normalized, and analytical data warehouse models.
Experience building scalable cloud-native data pipelines.
Experience with Git, CI/CD pipelines, and software engineering best practices.
Strong analytical, troubleshooting, and problem-solving skills.
Excellent communication and stakeholder collaboration skills.
Experience working within Agile development environments.
Google Cloud Platform (GCP)
Dataproc
BigQuery
SQL
dbt
ETL / ELT
Data Modeling
Cloud Data Engineering
Git
CI/CD
Agile Methodologies
Google Cloud Platform (GCP)
Dataproc
BigQuery
SQL
dbt
Git
CI/CD Pipelines
Data Warehousing
ETL / ELT Development
Cloud-native Data Architecture
Experience with Apache Airflow.
Experience integrating Apache Kafka or other streaming technologies.
Hands-on experience with PySpark.
Strong Python programming skills for data engineering and automation.
Experience with data quality, metadata management, and data governance.
Retail or Apparel industry experience.
Experience supporting Supply Chain, Transportation, Logistics, Warehouse Management Systems (WMS), or Distribution Center operations.
EMPLOYEE TYPE:
Contract
WORPLACE:
On-site
LOCATION:
San Francisco, CA