Job Description

Department Engineering and Technology
LevelExperienced (Individual Contributor)
LocationSingapore
The Engineering and Technology team is at the core of the Shopee platform development. The team is made up of a group of passionate engineers from all over the world, striving to build the best systems with the most suitable technologies. Our engineers do not merely solve problems at hand; We build foundations for a long-lasting future. We don't limit ourselves on what we can or can't do; we take matters into our own hands even if it means drilling down to the bottom layer of the computing platform. Shopee's hyper-growing business scale has transformed most "innocent" problems into huge technical challenges, and there is no better place to experience it first-hand if you love technologies as much as we do.

About the Team:

Marketplace Intelligence and Data Team
The mission of the Marketplace Intelligence and Data team is to build sustainable, efficient data and intelligence products that power Shopee's business growth. The team is responsible for Shopee's e-commerce data warehouse, merchant and operations data products, end-to-end traffic data, product algorithms (including product listing, governance, content optimization, SPU cataloging and price comparison), marketing algorithms (including merchant onboarding, assortment, and recommendations), review algorithms, user profiling, as well as foundational AI capabilities such as machine translation, speech processing, computer vision, and identity verification.

As the core horizontal data team supporting all algorithm teams within Marketplace Intelligence and Data, the Algorithm Data Team aims to be the most reliable strategic data partner for algorithm development. We are committed to delivering efficient, stable, and high-quality data services that accelerate algorithm iteration and transform data into strong commercial value for Shopee.

:

As an Algorithm Data Engineer, you will be responsible for transforming data into algorithmic productivity across the following key areas:
1. Unified Feature Platform Development
Lead or participate in the design, development, and maintenance of enterprise-level feature platforms/feature stores. Tackle challenges such as online/offline feature consistency, real-time processing, and high availability. Ensure standardization and automation of the feature engineering workflow to improve feature development efficiency for algorithm teams.

2. High-Quality Dataset Construction & Maintenance
Design and build high-performance, low-latency offline and real-time datasets for model training, evaluation, and inference. Optimize data pipelines and ETL processes to significantly enhance large-scale data processing efficiency and data quality.

3. Algorithm Experimentation & Monitoring Pipeline
Contribute to the development and maintenance of core data pipelines for algorithm experimentation. Provide end-to-end support--from data preparation, configuration, and runtime monitoring to metrics analysis and result evaluation.

4. High-Value Label & Graph Mining
Leverage deep understanding of e-commerce and algorithmic needs to extract high-value user profiles, product tags, and relationship graphs from massive behavioral data, effectively enabling both algorithms and business strategies.

5. Architecture Optimization & Technology Exploration
Continuously improve the data architecture, including real-time processing, unified batch-stream systems, multimodal data processing, and compute resource optimization. Maintain a cutting-edge and robust technology stack.

Requirements:

Bachelor's degree or above in Computer Science or a related field, with 5+ years of experience in big data. Hands-on experience with one or more big data technologies such as Spark, Flink, Hadoop, HBase, Kafka, Druid, ClickHouse, etc. Proficient in one or more programming languages, such as Python, Java, Scala, or SQL. Experience in data architecture design, data warehouse modeling, or performance tuning is preferred. Prior experience with feature platforms/feature stores, algorithm experimentation pipelines, or graph construction is a plus. Strong logical thinking, communication skills, and project coordination abilities * Strong self-motivation and resilience, with a willingness to experiment and drive business impact.