Senior Data Engineer

Sr. Data Engineer Location: Pleasanton & San Francisco, CA Duration: 6+ months of extendable contract Key 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 Required Technical Skills o Dataproc o BigQuery o SQL o 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) • Retail industry (Apparel) • Supply Chain data platforms • Transportation and Logistics • Warehouse Management Systems (WMS) • Distribution Center operations