Data Engineer: Scalable Retail Data Pipelines on GCP

Ambition; Hong Kong; On-site; HKD 420,000 - 640,000; Full time

Job summary

Ambition is seeking a Data Engineer in Hong Kong to design, build, and maintain scalable data pipelines and cloud-based data platforms that support business intelligence and analytics. The ideal candidate has hands-on experience with GCP technologies, strong programming and SQL skills, and experience working with large-scale retail data environments.

The role requires 3–5 years of data engineering experience, with a focus on ETL/ELT development, data warehousing, and data platform management.

Qualifications

• 3–5 years of Data Engineering experience.
• Experience with ETL/ELT, data warehousing, and data platform management.
• GCP experience preferred; AWS or Azure experience also considered.
• Proficient in SQL and Python/PySpark.
• Retail data experience preferred.

Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines and cloud-based data platforms.
• Ingest, transform, and manage high-volume retail data, including POS, e-commerce, inventory, and customer data.
• Optimize data workflows, storage, and processing performance for reliability and cost efficiency.
• Collaborate with business analysts and data teams to deliver analytics-ready datasets and reporting solutions.

Skills

ETL/ELT development

Data warehousing

Data modeling

SQL

Python / PySpark

Retail data domain

Languages: English Cantonese Mandarin

Tools

BigQuery

Dataflow

Cloud Storage

AWS

Azure

Job description

Ambition is seeking a Data Engineer in Hong Kong to design, build, and maintain scalable data pipelines and cloud-based data platforms that support business intelligence and analytics. The ideal candidate has hands-on experience with GCP technologies, strong programming and SQL skills, and experience working with large-scale retail data environments.

The role requires 3–5 years of data engineering experience, with a focus on ETL/ELT development, data warehousing, and data platform management.