Senior Data Engineer

Role Overview:
Data Analysts on the TW Logistics Analytics team are responsible for understanding and improving the entire customer delivery journey—from order placement to final delivery (last-mile logistics)—through data-driven insights.

What You Will Do:
End-to-End Delivery Operations Analytics

• Define and monitor key KPIs related to the delivery network, delivery status, and courier operations, and identify the root causes of operational issues through data-driven analysis.
• Track and analyze operational metrics such as delivery success rate, delivery lead time, and courier productivity, uncover improvement opportunities, and support data-driven decision-making within the Operations organization.

New Project Simulation & Pre-/Post-Launch Analysis

• Evaluate the impact of new initiatives, such as route optimization and network redesign, through rigorous pre- and post-launch data analysis.
• Design simulation frameworks and provide accurate, actionable insights to help decision-makers make informed business decisions.

Data Infrastructure & Governance

• Design, build, and maintain the data pipelines (Airflow DAGs) and data mart tables (Hive/Presto) that serve as the foundation for delivery-domain analytics.
• Ensure data integrity and reliability through validation, backfilling, and governance processes, while maintaining a trusted data ecosystem.

KPI Reporting & Stakeholder Communication

• Develop and manage business reports and dashboards for leadership teams and key stakeholders.
• Communicate analytical findings clearly and concisely to diverse audiences, fostering a data-driven decision-making culture across the organization.

Cross-Functional Collaboration

• Partner closely with Product Managers, Program Managers, Engineers, and Operations teams to translate business questions into analytical frameworks and deliver timely, actionable insights.

Essential Qualifications

• 3+ years of experience analyzing large-scale datasets using SQL (Presto/Hive).
• Experience developing data ETL processes and orchestrating data pipelines (e.g., Airflow).
• Experience building dashboards and business reports using tools such as Tableau, Power BI, or Zeppelin.
• Strong ability to identify, troubleshoot, and resolve data quality and validation issues.
• Proven ability to work effectively in cross-functional environments with Engineering, Product, and Operations teams.
• Excellent communication skills with the ability to clearly present analytical findings and recommendations to stakeholders.
• Business proficiency in Mandarin Chinese.
• Intermediate English proficiency, including reading, writing, and verbal communication.

Preferred Qualifications:

• Knowledge of logistics and delivery operations, including last-mile delivery, delivery network design, and Warehouse Management Systems (WMS).
• Understanding of statistical methodologies, including A/B testing and causal inference.
• Proficiency in Python for data analysis, automation, and workflow optimization.
• Experience working with diverse data systems in global and multi-market environments.
• Proven track record of leading end-to-end analytics projects, from problem definition and analysis design to insight generation and decision support.
• Experience leveraging AI/ML tools (e.g., LLM-based coding assistants, Generative AI) to improve analytics workflows, such as automated query generation, accelerated pipeline development, and automated insight summarization.