Data Engineer - Traffic Mart

Shopee • Commerce • Bachelor's Degree • Python • Java • SQL • Scala • 2 days ago
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Salary
≈ $59k – $149k per year (Estimated)
Location
In office (Singapore)
Seniority
Middle · 3+ years exp

Confirmed on the employer's own hiring board on Sep 26, 2026. First seen by Alion on Sep 24, 2026.

Overview
Company
Impact
Profile match

Shopee

Shopee is a multinational technology company and e-commerce marketplace platform operating as a subsidiary of Sea Limited. The company provides a hybrid B2C and C2C digital marketplace offering retail products, integrated digital payments and financial services via ShopeePay/SeaMoney, and end-to-end logistics and fulfillment solutions through SPX Express. Headquartered in Singapore, the platform serves millions of consumers and merchant partners across Southeast Asia, Taiwan, and Latin America.
shopee.com • HQ: Singapore • Commerce • 1001-5000 employees • Est. 2015
Tech stack of Shopee
  • Build and operate the Marketplace data warehouse end to end, covering batch and real-time ingestion, semantic layer design, and application-layer modeling for downstream consumers.
  • Collaborate with product, business, and engineering teams to translate requirements into scalable data architectures that support BI reporting, self-serve analytics, and algorithmic applications.
  • Design and optimize large-scale data processing pipelines, improving throughput, latency, and cost efficiency across offline and streaming platforms.
  • Lead data quality and governance efforts, including schema standardization, lineage tracking, SLA monitoring, and best practices that increase reliability and user trust.
  • Evaluate and adopt emerging data technologies such as streaming engines, lakehouse architectures, and AI/ML data stacks to address key Marketplace challenges and evolve the platform roadmap.
  • Bachelor's Degree or above in Computer Science or related fields
  • At least 3 years of data engineering experience
  • Prior experience or knowledge working with Traffic Mart would be advantageous
  • Experience with big data processing technologies such as Spark, Flink, Hadoop or HBase
  • Proficiency in one or more programming languages, such as Java, Scala, Python, SQL, etc.
  • Familiar with data warehouse architecture and principles
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