Primary Skills: Google Cloud Platform (GCP) (Expert), BigQuery & Dataproc (Expert), ETL/ELT & Data Pipeline Development (Expert), SQL & dbt (Expert), Data Modeling & Cloud Data Warehousing (Advanced)
Contract Type: W2 Only
Duration: 6+ Months
Location: San Francisco, CA
Pay Range: $65 - $68 on W2
Job Summary:
We are seeking an experienced
Lead Data Engineer – Data & AI, Supply Chain to design, develop, and deliver scalable cloud-native data platforms supporting Supply Chain analytics and AI initiatives. The ideal candidate will have deep expertise in
Google Cloud Platform (GCP), BigQuery, Dataproc, SQL, and dbt, with proven experience building enterprise-scale ETL/ELT pipelines, data models, and data products. This is a hands-on technical leadership role requiring close collaboration with Product Managers, Data Architects, Solution Architects, and business stakeholders to deliver high-performance data solutions across Sourcing, Transportation, and Warehouse Management (WMS).
Key Responsibilities:- Design, develop, and maintain scalable ETL/ELT pipelines and enterprise data products on Google Cloud Platform (GCP).
- Build and optimize cloud-native data solutions using BigQuery, Dataproc, SQL, and dbt.
- Design robust dimensional, normalized, and analytical data models to support reporting, analytics, and AI use cases.
- Develop scalable data ingestion, transformation, validation, and publishing pipelines from multiple enterprise source systems.
- Collaborate with Product Managers, Business Analysts, Data Architects, and Solution Architects to translate business requirements into technical solutions.
- Lead technical design discussions, perform code reviews, and establish engineering best practices.
- Optimize data processing performance, scalability, reliability, and cloud cost efficiency.
- Implement monitoring, testing, CI/CD, and operational best practices for production data workloads.
- Develop reusable frameworks, engineering standards, and technical documentation.
- Troubleshoot production issues and drive continuous platform improvements.
- Mentor engineers and actively participate in Agile ceremonies, sprint planning, backlog refinement, and estimation.
Must-have Skills:- 8+ years of Data Engineering experience with technical leadership on enterprise data platforms.
- Strong hands-on experience with Google Cloud Platform (GCP).
- Expert experience with BigQuery, Dataproc, SQL, and dbt.
- Strong experience designing and developing scalable ETL/ELT pipelines.
- Expertise in dimensional modeling, normalized data models, and cloud data warehouse architecture.
- Experience building cloud-native, scalable, and maintainable data pipelines.
- Experience with Git, CI/CD pipelines, and software engineering best practices.
- Excellent analytical, troubleshooting, and performance optimization skills.
- Strong communication skills with the ability to collaborate across technical and business teams.
Nice-to-have Skills:- Apache Airflow workflow orchestration.
- Apache Kafka or other event streaming technologies.
- PySpark for distributed data processing.
- Python for data engineering automation and utilities.
- Data quality, metadata management, and data governance.
- Retail, Supply Chain, Transportation, Logistics, Warehouse Management Systems (WMS), or Distribution Center domain experience.
Preferred Qualifications:- Bachelor's degree in Computer Science, Engineering, Information Systems, or related field.
- Experience delivering cloud-native data platforms supporting enterprise analytics and AI initiatives.
- Proven leadership in mentoring engineers and driving engineering best practices.
- Experience working within Agile software development environments.
- Strong understanding of Supply Chain, Retail, Transportation, or Warehouse Management business processes.
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