Data Engineer

Job Title: Lead Data Engineer

Locations: 2 Folsom, San Francisco, CA 94105

Job Type: 17 Months contract

Description:

Client seeks an experienced Lead Data Engineer to join the Supply Chain Data & AI organization. You will design, develop, and deliver enterprise data products and analytics solutions across Sourcing, Transportation, and Warehouse Management Systems (WMS). You will collaborate with Product Managers, Solution Architects, Data Architects, Business SMEs, and engineering teams to build scalable, cloud-native data platforms on GCP that enable analytics and AI-driven decision making. This role is onsite.

Responsibilities:

• Design, develop, and implement scalable data pipelines and data products on GCP .
• Build and optimize enterprise data solutions using Dataproc, BigQuery, SQL, and dbt.
• Design robust and scalable data models for analytical and operational reporting.
• Develop efficient ETL/ELT pipelines to ingest, transform, and publish data from multiple enterprise systems.
• Translate business requirements into scalable technical solutions in partnership with Product Managers, Business Analysts, and Architects.
• Lead technical design discussions and conduct code reviews to ensure quality and standards compliance.
• Optimize performance, reliability, scalability, and cost across cloud data platforms.
• Implement monitoring, testing, and operational best practices for production workloads.
• Contribute to reusable frameworks, engineering standards, and documentation.
• Support production issue resolution and continuous improvement.
• Work within Agile teams and participate in sprint planning, estimation, and backlog refinement.
• Mentor team members.

Required Skills & Qualifications:

• 8 years of experience in Data Engineering with technical leadership on enterprise data projects.
• Strong hands-on experience with GCP.
• Expert-level proficiency in Dataproc, BigQuery, SQL, and dbt.
• Strong understanding of modern ETL/ELT architectures and large-scale data processing.
• Knowledge of data modeling techniques, including dimensional and normalized models, and analytical warehouse design.
• Experience building scalable, maintainable cloud-native data pipelines.
• Experience with Git, CI/CD pipelines, and engineering best practices.
• Strong analytical, troubleshooting, and problem-solving skills.
• Excellent verbal and written communication skills for cross-functional collaboration.

Preferred Skills:

• Apache Airflow for workflow orchestration.
• Integration with Apache Kafka or similar streaming technologies.
• Working knowledge of PySpark for distributed processing.
• Proficiency in Python for data engineering and automation.
• Familiarity with data quality, metadata management, and data governance best practices.

Domain Experience (Highly Desirable):

• Retail industry (Apparel).
• Supply Chain data platforms.
• Transportation and Logistics.
• Warehouse Management Systems (WMS).
• Distribution Center operations.

Desired Attributes:

• Self-driven with the ability to work independently in a fast-paced environment.
• Ownership mindset with a focus on high-quality delivery.
• Ability to balance technical excellence with business priorities.
• Effective collaborator with business partners, architects, product managers, and engineering teams.
• Passion for building scalable, reliable, and reusable data solutions that enable analytics and AI across Supply Chain.