米哈游资深数据系统研发工程师(画像平台方向)
社招全职5年以上程序&技术类地点:上海状态:招聘
任职要求
1、计算机相关专业本科及以上学历,5年以上数据平台或后端研发经验,其中至少2年以上专注于用户画像、标签或DMP系统建设。 2、精通Java及Spring Boot等微服务框架,具备高并发、分布式系统设计及JVM调优经验。 3、深刻理解用户画像技术栈,熟悉标签建模、ID-Mapping、人群圈选等核心逻辑与实现方案。 4、熟练掌握Hive、Spark、Flink中至少一种大数据计算引擎,具备海量用户行为数据加工处理经验。 5、熟悉至少一种OLAP引擎(如,StarRocks, ClickHouse等),并有其在高并发查询场景下的性能优化经验。 6、具备多地域/多云(阿里云 + AWS)分布式系统的…
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工作职责
专注于用户画像平台的架构设计与核心功能开发。您将负责构建和维护支撑亿级用户的画像系统,包括人群包圈选、标签计算与服务、用户判存接口以及画像分析平台,为公司的精细化运营、个性化推荐和增长分析提供核心数据能力。 1、负责用户画像平台的后端架构设计与研发,核心覆盖人群包(灵活圈人、交并差计算)、标签体系(离线/实时标签计算、管理、服务化)、用户判存接口(高并发、低延迟的ID-Mapping与状态查询)以及画像数据分析模块。 2、设计并实现高可用、高扩展、低延迟的画像数据服务,优化从标签生产、人群计算到接口服务的全链路性能与稳定性。 3、与数据产品、算法、数仓及前端团队紧密协作,深入理解业务场景,将复杂的画像数据能力抽象为易用、高效的产品功能,降低业务方使用门槛。 4、持续优化画像数据存储与计算架构,探索基于Hive/ClickHouse/StarRocks等数据引擎或Bitmap等查询性能优化,平衡系统成本与效率。 5、负责画像相关数据链路的治理,保障标签数据的一致性、准确性及时效性。
包括英文材料
学历+
Java+
https://www.youtube.com/watch?v=eIrMbAQSU34
Master Java – a must-have language for software development, Android apps, and more! ☕️ This beginner-friendly course takes you from basics to real coding skills.
Spring Boot+
https://spring.io/guides/gs/spring-boot
his guide provides a sampling of how Spring Boot helps you accelerate application development.
https://www.youtube.com/watch?v=Nv2DERaMx-4&list=PLzUMQwCOrQTksiYqoumAQxuhPNa3HqasL
The author teaches you how to use Spring Boot from a complete beginner, to building a REST API with a real database, Dockerising it and deploying it to the cloud.
微服务+
https://learn.microsoft.com/en-us/training/modules/dotnet-microservices/
Microservice applications are composed of small, independently versioned, and scalable customer-focused services that communicate with each other by using standard protocols and well-defined interfaces.
https://microservices.io/
Microservices - also known as the microservice architecture - is an architectural style that structures an application as a collection of two or more services.
https://spring.io/microservices
Building small, self-contained, ready to run applications can bring great flexibility and added resilience to your code.
https://www.ibm.com/think/topics/microservices
Microservices, or microservices architecture, is a cloud-native architectural approach in which a single application is composed of many loosely coupled and independently deployable smaller components or services.
https://www.youtube.com/watch?v=CqCDOosvZIk
https://www.youtube.com/watch?v=hmkF77F9TLw
Learn about software system design and microservices.
高并发+
https://www.baeldung.com/concurrency-principles-patterns
In this tutorial, we’ll discuss some of the design principles and patterns that have been established over time to build highly concurrent applications.
https://www.baeldung.com/java-concurrency
Handling concurrency in an application can be a tricky process with many potential pitfalls. A solid grasp of the fundamentals will go a long way to help minimize these issues.
https://www.oreilly.com/library/view/concurrency-in-go/9781491941294/
You’ll understand how Go chooses to model concurrency, what issues arise from this model, and how you can compose primitives within this model to solve problems.
https://www.oreilly.com/library/view/modern-concurrency-in/9781098165406/
With this book, you'll explore the transformative world of Java 21's key feature: virtual threads.
https://www.youtube.com/watch?v=qyM8Pi1KiiM
https://www.youtube.com/watch?v=wEsPL50Uiyo
分布式系统+
https://www.distributedsystemscourse.com/
The home page of a free online class in distributed systems.
https://www.youtube.com/watch?v=7VbL89mKK3M&list=PLOE1GTZ5ouRPbpTnrZ3Wqjamfwn_Q5Y9A
JVM+
https://www.freecodecamp.org/news/jvm-tutorial-java-virtual-machine-architecture-explained-for-beginners/
https://www.youtube.com/watch?v=e2zmmkc5xI0
Hive+
[英文] Hive Tutorial
https://www.tutorialspoint.com/hive/index.htm
Hive is a data warehouse infrastructure tool to process structured data in Hadoop. It resides on top of Hadoop to summarize Big Data, and makes querying and analyzing easy.
https://www.youtube.com/watch?v=D4HqQ8-Ja9Y
Spark+
[英文] Learning Spark Book
https://pages.databricks.com/rs/094-YMS-629/images/LearningSpark2.0.pdf
This new edition has been updated to reflect Apache Spark’s evolution through Spark 2.x and Spark 3.0, including its expanded ecosystem of built-in and external data sources, machine learning, and streaming technologies with which Spark is tightly integrated.
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