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Salary
≈ $54k – $110k per year (Estimated)
Location
In office (Singapore)
Seniority
Senior · 5+ years exp

Confirmed on the employer's own hiring board on Nov 4, 2026. First seen by Alion on Sep 10, 2026.

Overview
Company
Impact
Profile match
SHOPLINE is an omnichannel commerce Software-as-a-Service (SaaS) provider and smart retail platform. Headquartered in Singapore - with major operational hubs across Hong Kong, Taiwan, China, Australia, and the UK - the enterprise provides cloud-based software for independent brands, retailers, and online merchants.
Backed by 500 Global

Data Engineer - SHOPLINE Singapore

SHOPLINE is Asia’s largest smart commerce platform. With our customers in mind, we strive to deliver scalable commerce solutions to merchants of all sizes. We’re a full-featured platform with services including online store opening, O2O solution, retail POS systems, advertising placement, business strategy consultation, marketing, and more to empower merchants to succeed in omnichannel retailing and cross-border commerce.

What you’ll be doing:

  • Responsible for collecting, designing, storing and processing payments data in the eCommerce business. In charge of unifying and standardizing data to create holistic business digital assets.

  • Play a leading role in constructing business evaluation metrics, developing tactics in data services and creating data-driven tools in alignment with Products and Operations objectives.

  • Define underlying business data requirements. Build fitted models to enhance data quality and stability. Standardize and maintain data integrity to provide an efficient way in accessing data.

Who we are looking for:

  • 5+ years of experience as a data engineer with a bachelor or advanced in Computer Science. Proven track record in data warehousing.

  • Demonstrated strength in data modeling, development and governance. Preferred experience with building ETL pipelines.

  • Expert skills in SQL and Python. Familiarity with big data technologies and solutions (Spark, Hadoop, Hive, etc.). Nice to have a background in Machine Learning.

  • Proven success in communicating across different functions and synthesizing resources to push through projects in a dynamic environment.

  • Preferred experience in tech firms, especially in the payments industry.

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