[Remote] Data Engineer
Note: The job is a remote job and is open to candidates in USA. eTeam 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 various domains.
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
Skills
- 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
- 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
- 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
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