Our Client, an American Multinational Clothing and Accessories Retailer company, is looking for a Lead Data Engineer - Data & AI, Supply Chain for their San Francisco, CA location.
Responsibilities:
- Design, develop, and implement scalable data pipelines and data products on Google Cloud Platform (GCP).
- Build and optimize enterprise data solutions using Dataproc, BigQuery, SQL, and dbt.
- Design robust and scalable data models that support analytical and operational reporting requirements.
- Develop efficient ETL/ELT pipelines to ingest, transform, and publish data from multiple enterprise systems.
- Collaborate with Product Managers, Business Analysts, Enterprise Solution Architects, Data Architects, and business stakeholders to translate business requirements into scalable technical solutions.
- Lead technical design discussions and perform code reviews to ensure engineering quality and adherence to standards.
- Optimize data processing performance, reliability, scalability, and cost across cloud-based data platforms.
- Implement monitoring, testing, and operational best practices to support production workloads.
- Contribute to reusable frameworks, engineering standards, and documentation that improve team productivity and solution consistency.
- Support production issue resolution and continuous improvement initiatives.
- Work effectively within Agile delivery teams and participate in sprint planning, estimation, and backlog refinement.
- Mentor team members
Requirements:
- 8+ years of experience in Data Engineering with demonstrated technical leadership on enterprise data projects.
- Strong hands-on experience with Google Cloud Platform (GCP).
- Expert-level proficiency in:
- Dataproc
- BigQuery
- SQL
- dbt (Data Build Tool)
- Strong understanding of modern ETL/ELT architecture and large-scale data processing.
- Strong knowledge of data modeling techniques, including dimensional modeling, normalized data models, and analytical data warehouse design.
- Experience building scalable and 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 with the ability to collaborate effectively across cross-functional teams.
- Preferred Technical Skills
- Experience with Apache Airflow for workflow orchestration.
- Experience integrating enterprise data platforms with Apache Kafka or other streaming technologies.
- Working knowledge of PySpark for distributed data processing.
- Proficiency in Python for data engineering, automation, and utility development.
- Familiarity with data quality, metadata management, and data governance best practices.
- Domain Experience (Highly Desirable)
- Candidates with experience in one or more of the following areas will be strongly preferred:
- Retail industry (Apparel)
- Supply Chain data platforms
- Transportation and Logistics
- Warehouse Management Systems (WMS)
- Distribution Center operations
- Desired Attributes
- Self-driven and able to work independently in a fast-paced environment.
- Strong ownership mindset with a focus on delivering high-quality solutions.
- Ability to balance technical excellence with business priorities.
- Effective collaborator who can work seamlessly with business partners, architects, product managers, and engineering teams.
- Passion for building scalable, reliable, and reusable data solutions that enable analytics and AI capabilities across the Supply Chain organization.
Why Should You Apply?
- Health Benefits
- Referral Program
- Excellent growth and advancement opportunities
Lead Data Engineer - Data & AI, Supply Chain in Remote at Unknown Company
This position is listed as full time and onsite.