Job Title: Data Engineer
Location: Remote - PST time zone
Duration: Contract - 17 months
Job Description
We are seeking a Data Engineer to join our Supply Chain Data & AI organization. The ideal candidate will have strong experience in building cloud-native data products and pipelines on Google Cloud Platform using BigQuery, Dataproc, SQL, and dbt and a proven ability to deliver scalable, reliable data models and pipelines that power analytics and AI across Sourcing, Transportation, and Warehouse Management.
Responsibilities:
- Design, develop, and maintain scalable ETL/ELT pipelines on Google Cloud Platform.
- Build and optimize data solutions using Dataproc, BigQuery, SQL, and dbt.
- Develop and maintain high-quality data models for reporting, analytics, and AI.
- Ingest, transform, validate, and publish data from multiple enterprise source systems.
- Collaborate with product managers, business analysts, architects, and engineers to deliver scalable data solutions.
- Create reusable transformation components and follow engineering standards and best practices.
- Optimize data processing performance, reliability, and cost efficiency.
- Perform unit testing, data validation, and production support to ensure quality and stability.
- Participate in Agile ceremonies including sprint planning, backlog refinement, and code reviews.
- Document technical designs, data flows, and implementation details.
Required Skills & Qualifications:
- Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field, or equivalent experience.
- 4+ years of experience in data engineering.
- Hands-on experience delivering data solutions on Google Cloud Platform.
- Proficiency with Dataproc, BigQuery, SQL, and dbt.
- Strong knowledge of data modeling, including dimensional modeling and analytical warehousing concepts.
- Experience building scalable ETL/ELT pipelines and processing large datasets.
- Familiarity with Git-based version control and CI/CD practices.
- Analytical, troubleshooting, and problem-solving skills.
- Effective communication and collaboration abilities.
- Apache Airflow for workflow orchestration.
- Apache Kafka or other event streaming platforms.
- PySpark for distributed data processing.
- Python for data engineering, scripting, and automation.
- Understanding of data quality, metadata management, and data governance.
Domain Experience (Highly Desirable):
- Retail industry, especially apparel.
- Supply chain data platforms.
- Transportation and logistics.
- Warehouse Management Systems (WMS).
- Distribution center operations.