OneBullEx

Senior Batch Data Engineer (Alibaba Cloud Stack)

OneBullEx Dubai, Dubai, United Arab Emirates

Blockchain Services · 51-200 employees

7 h ago
data-engineer Senior (5-10 yrs) Full-time United Arab Emirates
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About the role

Design, build, and maintain scalable batch data pipelines and enterprise data warehouse layers using Alibaba Cloud services. Implement strict data quality monitoring, automated validation, and AI-assisted engineering workflows to support business analytics and AI/ML services.

What they look for

Alibaba Cloud DataWorks MaxCompute Hologres ETL/ELT Data Warehousing SQL Python Data Modeling Data Quality Pipeline Architecture AI-assisted Engineering GitHub Copilot Lark Data Engineering Cloud Computing

Requirements

Requires 5+ years of hands-on experience with Alibaba Cloud data services and advanced proficiency in SQL and Python. Candidates must be fluent in both English and Chinese to facilitate cross-functional technical collaboration.

Full description

OneBullEx is looking for a highly accountable, self-driven Senior Batch Data Engineer to take end-to-end ownership of our enterprise batch data warehouse on Alibaba Cloud. In this role, you will design, maintain, and optimise batch pipelines (T-1) supporting executive dashboards, business analytics, and AI/ML services — leveraging modern AI-assisted engineering techniques to rapidly build data layers (ODS, DWD, DWS, ADS) and enforcing strict data quality, automated validation, and proactive monitoring across the platform.

Key Responsibilities

Pipeline Architecture & Data Warehouse Modelling

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

AI-Accelerated Engineering & Testing

  • Integrate modern AI tools and techniques (e.g. Claude, GitHub Copilot, prompt engineering) into daily workflow to accelerate code generation, SQL refactoring, and data validation.
  • Apply new AI testing methodologies to rapidly write unit tests, simulate data scenarios, and audit data accuracy prior to production release.

Data Quality, Monitoring & Alerting

  • Implement strict data quality rules, automated reconciliation scripts, and validation checks directly inside DataWorks jobs.
  • Build proactive alerting and monitoring workflows (integrated with Lark) to detect data drift, schema breaks, or pipeline failures before business impact occurs.
  • Support downstream analytics, BI reporting, and AI/LLM services with clean, trusted datasets.

End-to-End Ownership & Collaboration

  • Take full ownership of daily T-1 batch pipeline stability, job scheduling, historical backfills, and legacy issue cleanup.
  • Act as a bilingual technical bridge, collaborating fluently in both English and Chinese with cross-functional technical leads, product managers, and developers.

Required Qualifications

  • 5+ years of hands-on expertise with Alibaba Cloud data services: DataWorks, MaxCompute, DTS, Hologres, FC Functions, Data Agents, and MaxCompute Lakehouse architectures.
  • Advanced proficiency in SQL and Python for data engineering, performance tuning, and database optimisation.
  • Proven experience modelling multi-layer enterprise data structures (ODS, DWD, DWS, ADS) and managing batch Lakehouse architectures.
  • Fluent in both English and Chinese, spoken and written, for seamless technical collaboration with regional teams.
  • Strong sense of ownership, high velocity, proactive communication, and a "deliver fast, iterate continuously" attitude.

Preferred

  • Active experience leveraging AI coding assistants (Copilot, LLMs) to speed up ETL development, code reviews, and query optimisation.
  • Experience building alerting and monitoring integrations with Lark or a similar collaboration platform.
  • Track record applying AI-driven testing methodologies ahead of production release.

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