Big Data Development Engineer

Job Responsibilities

Warehouse Construction & Optimization: Responsible for the construction and optimization of the group-level public data warehouse (Offline & Real-time) to consolidate unified data assets.

Tag System Development: Lead the construction of the tag system, developing both real-time and offline tagging capabilities to support business activities and precision user outreach.

Feature Engineering: Design and develop user and product feature libraries; collaborate with algorithm teams to drive the implementation of personalized recommendations and intelligent applications.

Modeling & Architecture: Gain a deep understanding of business requirements to complete data warehouse modeling and data asset design, ensuring the reusability and scalability of platform data.

Data Governance: Establish systems for data cleaning, quality monitoring, and alerting to continuously improve the accuracy and stability of data delivery.

Job Requirements

Education: Bachelor’s degree or above in Computer Science, Mathematics, Statistics, or related fields.

Technical Experience: At least 2 years of experience in data warehouse development. Expert proficiency in SQL with extensive experience in SQL optimization and familiarity with big data engines such as SparkSQL.

Core Knowledge: Deep understanding of Data Warehouse and BI systems, including ETL, data warehouse architecture, OLAP, and multidimensional modeling.

Programming Skills: Proficiency in at least one programming language among Python, Scala, or Java, with strong engineering capabilities.

Ecosystem Familiarity: Preferred experience with the big data ecosystem, including Hadoop, Hive, Spark, Flink, Kafka, Trino, Doris, or TiDB.

Soft Skills: Rigorous work ethic, excellent logical thinking and learning abilities. Skilled in communication and teamwork with the ability to independently drive the resolution of complex issue.