Senior Batch Data Engineer (Alibaba Cloud Stack)

Role Overview

Pipeline Architecture and Modelling

• Design, build, and maintain scalable ETL/ELT batch pipelines using Alibaba Cloud DataWorks and MaxCompute.
• Build ODS, DWD, DWS, and ADS enterprise data warehouse layers with modular SQL and Python scripts.
• Develop and optimise ingestion, transformation, and batch processing across MaxCompute, Hologres, DataWorks, DTS, and Lakehouse architectures.
• Ensure data reliability, query performance, schema stability, and cost-effective cloud resource usage.

AI-Accelerated Engineering and Testing

• Use Claude, GitHub Copilot, prompt engineering, and related AI techniques to accelerate code generation, SQL refactoring, and data validation.
• Write unit tests, simulate data scenarios, and audit data accuracy before production release.

Data Quality and Monitoring

• Implement data quality rules, reconciliation scripts, and validation checks inside DataWorks jobs.
• Build Lark-integrated monitoring and alerting workflows for data drift, schema breaks, and pipeline failures.
• Support downstream analytics, BI reporting, and AI/LLM services with clean, trusted datasets.

Ownership and Collaboration

• Own daily T-1 batch pipeline stability, job scheduling, historical backfills, and legacy issue cleanup.
• Collaborate in English and Chinese with technical leads, product managers, and developers.

Required Qualifications

• Requires 5+ years of hands-on experience with Alibaba Cloud data services and MaxCompute Lakehouse architectures.
• Requires advanced SQL and Python proficiency for data engineering, performance tuning, and database optimisation.
• Requires experience modelling ODS, DWD, DWS, and ADS enterprise data structures.
• Requires fluency in spoken and written English and Chinese.
• Requires strong ownership, proactive communication, and a high-velocity delivery attitude.

Preferred Qualifications

• Experience using AI coding assistants such as Copilot or LLMs is preferred.
• Experience integrating Lark or a similar collaboration platform for alerting and monitoring is preferred.
• Experience applying AI-driven testing methodologies before production release is preferred.