Senior Data Engineer - Square (APAC Remote)

• →Responsible for designing, building, and maintaining scalable data pipelines to support Square team’s data and feature engineering needs.
• →Lead feature data preparation, transformation, validation, and monitoring for machine learning and recommendation/search systems.
• →Collaborate closely with algorithm, product, and business teams to translate business requirements into reliable data and feature solutions.
• →Drive the development of core data infrastructure and feature platforms with data-driven strategies to maximize business impact.
• →Ensure data quality, stability, and performance across offline and online feature pipelines.
• →Identify data gaps and optimization opportunities, and define success metrics together with Product and Business stakeholders.

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, Software Engineering, or related fields, with 5+ years of relevant industry experience.
• Strong hands-on experience in data engineering, including large-scale data processing, ETL/ELT pipelines, and feature engineering.
• Expert-level proficiency in Java and Scala.
• Solid experience with big data technologies (e.g. Spark, Hive, Flink, or similar distributed systems).
• Familiar with machine learning feature lifecycle, including offline training features and online serving features.
• Experience working with data warehouses and feature stores is a strong plus.
• Bilingual English and Chinese are required to be able to coordinate with overseas partners and stakeholders.
• Strong ownership, communication skills, and ability to work in a fast-paced, cross-functional environment.

• Shape the future of finance 
• Collaborate with world-class talent in a user-centric global organization with a flat structure
• Tackle challenging projects in a fast-paced and innovative enviornment with autonomy
• Thrive in a results-driven workplace with opportunities for career growth and continuous learning
• Competitive salary and company benefits
• Remote-first, work-from-home arrangement (may vary depending on the nature of the role and team)

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