Data Engineer

Collaborate with Product Managers, Business Analysts, Data Architects, and engineering teams to understand business requirements and deliver scalable data solutions. Perform unit testing, data validation, and production support to ensure data quality and operational stability.

Our Client, an American Multinational Clothing and Accessories Retailer company, is looking for a Data Engineer for their San Francisco, CA location.
 
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
• 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

 
Why Should You Apply?

• Health Benefits
• Referral Program
• Excellent growth and advancement opportunities