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Data Engineer AI & Supply Chain : 26-02169

San Francisco, CA 94105

Posted: 08/04/2026 Job Category: Data Engineering, Big Data & Hadoop Job Number: 26-02169 Country: US

Job Description

Primary Skills: Google Cloud Platform (GCP) Data Engineering (Expert), BigQuery, Dataproc & dbt (Advanced), ETL/ELT Pipeline Development (Expert), SQL & Data Modeling (Advanced), Supply Chain Data Engineering (Advanced)
Contract Type: W2 Only
Duration: 6+ Months
Location: San Francisco, CA Remote (PST Time Zone)
Pay Range: $38 - $41 on W2

Job Summary:
We are seeking a skilled Data Engineer – Data & AI, Supply Chain to join the Supply Chain Data & AI organization. This role focuses on designing, developing, and maintaining scalable cloud-native data pipelines and data products on Google Cloud Platform (GCP) that power enterprise analytics and AI initiatives across Sourcing, Transportation, and Warehouse Management (WMS). The ideal candidate has strong hands-on experience with BigQuery, Dataproc, SQL, and dbt, along with expertise in building modern ETL/ELT solutions and scalable data platforms.
Key Responsibilities:
  • Design, develop, and maintain scalable ETL/ELT pipelines on Google Cloud Platform (GCP).
  • Build and optimize cloud-native data solutions using BigQuery, Dataproc, SQL, and dbt.
  • Design and maintain high-quality data models supporting enterprise reporting, analytics, and AI use cases.
  • Ingest, transform, validate, and publish data from multiple enterprise source systems.
  • Collaborate with Product Managers, Business Analysts, Data Architects, Solution Architects, and engineering teams to translate business requirements into scalable technical solutions.
  • Develop reusable data transformation frameworks while adhering to engineering standards and best practices.
  • Optimize data processing performance, scalability, reliability, and cloud cost efficiency.
  • Perform unit testing, data validation, production support, and troubleshooting to ensure high-quality data delivery.
  • Participate in Agile ceremonies including sprint planning, backlog refinement, code reviews, and technical discussions.
  • Create and maintain technical documentation, data flow diagrams, and implementation artifacts.
Must-have Skills:
  • Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field (or equivalent practical experience).
  • 4+ years of Data Engineering experience developing enterprise data solutions.
  • Strong hands-on experience with Google Cloud Platform (GCP).
  • Expertise with BigQuery, Dataproc, SQL, and dbt (Data Build Tool).
  • Strong understanding of ETL/ELT architecture and large-scale data processing.
  • Experience with dimensional data modeling and analytical data warehouse concepts.
  • Experience building scalable cloud-native data pipelines.
  • Knowledge of Git, version control, and CI/CD best practices.
  • Strong analytical, troubleshooting, problem-solving, and communication skills.
  • Experience working in Agile development environments.
Nice-to-have Skills:
  • Experience with Apache Airflow for workflow orchestration.
  • Experience integrating with Apache Kafka or other event-streaming platforms.
  • Working knowledge of PySpark for distributed data processing.
  • Proficiency in Python for data engineering, automation, and scripting.
  • Knowledge of data governance, metadata management, and data quality frameworks.
  • Experience supporting analytics, AI, or machine learning data platforms.
Preferred Qualifications:
  • Experience working within Retail, Apparel, Supply Chain, Transportation, Logistics, Warehouse Management Systems (WMS), or Distribution Center Operations.
  • Experience delivering enterprise cloud data solutions using modern GCP technologies.
  • Strong understanding of scalable data architecture and cloud-native engineering best practices.
  • Self-motivated team player with excellent collaboration skills and a passion for building reliable, high-performance data solutions.
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