Data Engineer - AI 30-35K

Michael Page International (Hong Kong) Limited; Hong Kong; On-site; HKD 334,800 - 502,200; Full time

Benefits offered by this job

Competitive monthly salary and benefits package

Exposure to cutting-edge technology and tools

Collaborative and inclusive work environment

Chance to contribute to impactful projects

Job summary

A business services organization in Hong Kong is seeking a skilled Data Engineer to design and deliver data solutions while managing ETL pipelines. The candidate should have at least 3 years of experience in data engineering, strong SQL capabilities, and practical knowledge of Apache Spark and Python. This role offers exposure to modern data platforms and a collaborative work environment, along with a competitive salary and benefits package.

Qualifications

• At least 3 years of hands-on experience in data engineering or related roles.
• Strong background in ETL development, data validation, and schema design.
• Solid SQL skills with experience in query tuning and optimization.
• Practical experience with Apache Spark and Python for data processing.
• Familiar with data pipeline tools such as Azure Data Factory, Kettle, or similar.
• Experience across various databases including MS SQL Server, PostgreSQL, MySQL, MongoDB, or Neo4J.

Responsibilities

• Design and deliver end-to-end data solutions covering validation, transformation, and retrieval.
• Handle diverse data types including structured, unstructured, and vector data.
• Build, deploy, and maintain data infrastructure within project scope.
• Develop and manage ETL pipelines and data schemas to support analytics and AI use cases.
• Implement and support data operations using notebooks and automation tools.
• Provide data engineering expertise and support to non-technical stakeholders.
• Ensure data reliability, performance, and scalability across platforms.

Skills

Data engineering

ETL development

SQL

Apache Spark

Python

Data Pipeline Tools

DevOps tools

Communication skills (Cantonese & English)

Tools

Azure Data Factory

Git

Docker

CI/CD

Snowflake

Databricks

DBT

Job description

• Work on modern data platforms and GenAI-driven solutions
• Hands‑on exposure to RAG, Spark, and cloud data engineering

About Our Client

Our client is a well-established organization within the business services industry, recognized for its commitment to innovation and excellence. They are a large organization with a global presence and a focus on leveraging technology to drive business success.

Job Description

• Design and deliver end-to-end data solutions covering validation, transformation, and retrieval.
• Handle diverse data types including structured, unstructured, and vector data.
• Build, deploy, and maintain data infrastructure within project scope.
• Develop and manage ETL pipelines and data schemas to support analytics and AI use cases.
• Implement and support data operations using notebooks and automation tools.
• Enable and maintain RAG solutions for LLM‑based applications.
• Provide data engineering expertise and support to non‑technical stakeholders.
• Ensure data reliability, performance, and scalability across platforms.

The Successful Applicant

• At least 3 years of hands‑on experience in data engineering or related roles.
• Strong background in ETL development, data validation, and schema design.
• Solid SQL skills with experience in query tuning and optimization.
• Practical experience with Apache Spark and Python for data processing.
• Familiar with data pipeline tools such as Azure Data Factory, Kettle, or similar.
• Experience across databases including MS SQL Server, PostgreSQL, MySQL, MongoDB, or Neo4J.
• Proven exposure to data embedding models and RAG implementations.
• Experience with modern data platforms, especially Microsoft Fabric.
• Knowledge of Snowflake, Databricks, or DBT is highly advantageous.
• Comfortable with DevOps tools such as Git, Docker, and CI/CD for DataOps.
• Strong communication skills in both Cantonese and English, business‑facing.

What's on Offer

• Competitive monthly salary and benefits package.
• Exposure to cutting‑edge technology and tools within the technology department.
• Collaborative and inclusive work environment.
• Chance to contribute to impactful projects and enhance your data engineering expertise.

If you are passionate about data engineering and looking for an exciting opportunity in the business services industry, we encourage you to apply!