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Shopee Hiring! Full Time Data Engineer - Traffic Mart in - Ricebowl

Data Engineer - Traffic Mart

Singapore

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Working Location

  • Singapore

Job Description

Responsibilities

About The Team

The Marketplace Intelligence and Data team's mission is to build sustainable and efficient data and intelligence products to facilitate Shopee's business development. The team is responsible for Shopee e-commerce data warehouse construction, merchant and operation data product construction, all-link traffic data, product algorithms, including product release, control, information optimization, SPU library and its comparison business, marketing algorithms, including Merchandising, Product Selection, Recommendation Algorithm, Evaluation Algorithms, User Profiling, and in addition, basic AI capabilities, such as Machine Translation, Speech Algorithm, Image Algorithm, and Real-person Authentication.

Job Description

  • Participate in the development work related to the Marketplace data warehouse, including data collection in offline and real-time data warehouses, data public layer construction, data application layer construction, and data governance.
  • Participate in supporting the data application of various business modules, cooperate with different teams to communicate the requirement, and design data architecture to provide data users with efficient data solutions, including supporting various scenarios such as BI analysis, data products, and algorithm applications.
  • Participate in the exploration and breakthrough of Marketplace's key data technologies, and be responsible for optimizing and improving the existing data architecture, improving data quality and productivity, and including massive data processing, real-time data processing, and the application of various new technologies.

Requirements

  • 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
  • Familiarity with one or more big data processing technologies such as Spark, Flink, Hadoop, HBase, Kafka, Druid, Clickhouse, etc.
  • Proficiency in one or more programming languages, such as Java, Scala, Python, SQL, etc.
  • Familiar with data warehouse architecture and principles, with relevant experience in big data architecture design, model design and performance tuning

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