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java etl scala spark flink📋 Description
- Design, build, and maintain scalable data pipelines for data and feature engineering.
- Lead feature data prep, transformation, validation, and monitoring for ML systems.
- Collaborate with algorithm, product, and business teams to implement data features.
- Drive core data infrastructure and feature platforms with a data-driven strategy.
- Ensure data quality, stability, and performance across offline and online feature pipelines.
- Identify data gaps and optimization opportunities; define success metrics with Product/Business.
🎯 Requirements
- Bachelor's or Master's in CS/Data/Software Eng, with 5+ years.
- Strong hands-on data engineering, ETL/ELT pipelines, and feature engineering.
- Expert-level proficiency in Java and Scala.
- Big data technologies (Spark, Hive, Flink) or similar distributed systems.
- Familiar with ML feature lifecycle (offline training features and online serving).
- Experience with data warehouses and feature stores is a strong plus.
- Bilingual English and Chinese to coordinate with overseas partners.
- Ownership, communication, and ability to work in fast-paced cross-functional teams.
🎁 Benefits
- Work-from-home arrangement (may vary by team).
- Competitive salary and company benefits.
- Equal opportunity employer.
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