Software Engineer (Big Data) - Application Computing
Aug 27, 2025 Singapore
About us
TikTok is the leading destination for short-form mobile video and our mission is to inspire creativity and bring joy.
- Size: 10,000+ employees
- Industry: Technology: Consumer Internet
Why you should apply for a job to TikTok:
4.5/5 in overall job satisfaction
4.5/5 in supportive management
100% say women are treated fairly and equally to men
100% would recommend this company to other women
100% say the CEO supports gender diversity
Ratings are based on anonymous reviews by Fairygodboss members. See all reviews ›
Responsibilities
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.
Qualifications
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.
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.
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.
Qualifications
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.
Responsibilities
ResponsibilitiesTeam 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.
Qualifications
QualificationsMinimum 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.
Additional Information
- Posted: Aug 27, 2025