Data Engineer

Russell Tobin is a leading minority-owned professional and technical recruitment and staffing advisory organization. They are seeking a skilled Data Engineer to join the Supply Chain Data & AI Organization, focusing on developing and supporting scalable data products and pipelines that enable analytics and AI initiatives.

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

Requirements:

• 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
• Strong experience with BigQuery
• Strong experience with SQL
• Strong experience with 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
• 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