- 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!
Contact: Michael Loe
Quote job ref: JN-042026-6993060
