Software Engineer (Big Data) - Application Computing

Team Introduction TikTok's Recommendation Architecture Team is responsible for real-time computing direction, handling the design and development of real-time computing systems for TikTok videos, live streams, e-commerce, and a billion-user product recommendation system. Their main focus is ensuring system stability and high availability. They abstract general real-time computing systems, build a unified recommendation feature middleware, and implement a flexible and scalable high-performance storage system and computing model. This enables advanced real-time data systems for deduplication, counting, feature services, and other recommendation-related business needs.

Responsibilities: - Design and implement real-time (streaming computing) data systems for large-scale recommendation systems. - Create flexible, scalable, stable, and high-performance storage systems and computing models. - Troubleshoot production system failures, design and implement necessary mechanisms and tools to ensure overall stability of the production systems - Construct industry-leading streaming computing frameworks and other distributed systems to provide reliable infrastructure for massive data and large-scale business systems - Research, design, and develop computer and network software or specialised utility programs. - Analyse user needs and develop software solutions, applying principles and techniques of computer science, engineering, and mathematical analysis. - Update software, enhances existing software capabilities, and develops and direct software testing and validation procedures. - Work with computer hardware engineers to integrate hardware and software systems and develop specifications and performance requirements.

Minimum Qualifications - Proficient in programming languages like Java, C++, Scala, Python. - Strong coding and troubleshooting skills. - At least 5 years of relevant experience - Deep understanding of streaming computing systems, with formal production experience in developing TB-level Flink real-time computing systems. Proficient in modules like FlinkDataStream, FlinkSQL, FlinkCheckpoint, FlinkState, and preferably with experience in reading Flink source code. - Experience in data lake development is preferred. Familiar with at least one data lake technology such as Hudi, Iceberg, DeltaLake, and preferably with experience in reading their source code. - Willingness to tackle problems without clear answers, with a strong passion for learning new technologies.

Preferred Qualifications - Experience in handling PB-level data is a plus. - Familiarity with other big data systems is preferred, including YARN, K8S, Spark, SparkSQL, Kudu, and others. - Experience in storage systems such as Hbase, Cassandra, RocksDB.