Data Engineer

Job Title: Data Engineer Data & AI, Supply Chain
Location: Remote - US
Duration: 18 Months Contract

About the Role
Client is seeking a skilled Data Engineer to join the Supply Chain Data & AI Organization. This role will focus on developing and supporting scalable data products and data pipelines that enable analytics and AI initiatives across the Sourcing, Transportation, and Warehouse Management (WMS) domains.

As a Data Engineer, you will work closely with Product Managers, Data Architects, Solution Architects, Business Analysts, and fellow engineers to design, build, test, and maintain cloud-native data solutions on Google Cloud Platform (GCP). You will play a key role in transforming enterprise data into trusted, high-quality data assets that drive business insights and operational excellence.

Key Responsibilities
Design, develop, and maintain scalable ETL/ELT data pipelines on Google Cloud Platform (GCP).
Build and optimize data solutions using Dataproc, BigQuery, SQL, and dbt.
Develop and maintain high-quality data models that support 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, and engineering teams to understand business requirements and deliver scalable data solutions.
Develop reusable data transformation components and adhere to established engineering standards and best practices.
Optimize data processing performance, reliability, and cost efficiency.
Perform unit testing, data validation, and production support to ensure data quality and operational stability.
Participate in Agile ceremonies, including sprint planning, backlog refinement, and code reviews.
Document technical designs, data flows, and implementation details.

Required Qualifications
Bachelor s degree in Computer Science, Engineering, Information Systems, or a related field, or equivalent practical experience.
4 years of experience in Data Engineering.
Hands-on experience developing data solutions on Google Cloud Platform (GCP).

Strong experience with:
Dataproc
BigQuery
SQL
dbt (Data Build Tool)
Strong knowledge of data modeling techniques, including dimensional modeling and analytical data warehouse concepts.
Experience building scalable ETL/ELT pipelines and processing large datasets.
Familiarity with software development best practices, including Git-based version control and CI/CD.
Strong analytical, troubleshooting, and problem-solving skills.
Excellent communication and collaboration skills.

Preferred Qualifications
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.
Experience using Python for data engineering, scripting, and automation.
Knowledge of data quality, metadata management, and data governance principles.
Domain Experience (Highly Desirable)
Experience in one or more of the following domains is highly desirable:
Retail industry (Apparel)
Supply Chain data platforms
Transportation and Logistics
Warehouse Management Systems (WMS)
Distribution Center operations
Desired Attributes
Strong problem-solving and analytical skills.
Ability to work independently while collaborating effectively within cross-functional Agile teams.
Commitment to delivering high-quality, reliable, and scalable data solutions.
Eagerness to learn new technologies and continuously improve engineering practices.
Customer-focused mindset with the ability to translate business requirements into effective technical solutions.