拼多多【商业化】搜索、推荐、广告数据开发工程师
社招全职技术类地点：上海状态：招聘
任职要求
1、精通数据仓库模型设计与Kimball维度建模方法论，具备丰富的ETL开发及海量数据加工处理经验； 2、具备丰富的Flink实时计算开发与调优经验，精通高并发、高可用、可扩展分布式系统设计原则与实践； 3、具备分布式数据存储与计算平台(Hadoop生态)应用开发经验，熟练掌握HDFS, MapReduce, Hive, HBase等核心技术者优先； 4、具有电商行业经验，优秀的业务理解能力与商业敏感度，能通过数据模型洞察业务问题并驱动目标达成； 5、了解常用机器学习算法及数据建模流程，有搜索/推荐场景应用经验者优先。
工作职责
1、负责电商搜索、广告、推荐等核心业务数据体系及相关工具平台的规划、建设与持续优化，高效支持算法、分析、工程等团队的数据需求； 2、深入理解业务逻辑，抽象业务需求并设计可扩展、高性能的数据技术架构，快速响应业务变化，构建高效、可靠的数据互通与共享机制； 3、负责数据处理链路（离线/实时）的日常运维、监控与保障，确保数据稳定、高效产出，及时解决数据问题。
包括英文材料
数据仓库+
https://www.youtube.com/watch?v=9GVqKuTVANE
From Zero to Data Warehouse Hero: A Full SQL Project Walkthrough and Real Industry Experience!
https://www.youtube.com/watch?v=k4tK2ttdSDg
ETL+
https://www.ibm.com/think/topics/etl
ETL—meaning extract, transform, load—is a data integration process that combines, cleans and organizes data from multiple sources into a single, consistent data set for storage in a data warehouse, data lake or other target system.
https://www.youtube.com/watch?v=OW5OgsLpDCQ
It explains what ETL is and what it can do for you to improve your data analysis and productivity.
Flink+
https://nightlies.apache.org/flink/flink-docs-release-2.0/docs/learn-flink/overview/
This training presents an introduction to Apache Flink that includes just enough to get you started writing scalable streaming ETL, analytics, and event-driven applications, while leaving out a lot of (ultimately important) details.
https://www.youtube.com/watch?v=WajYe9iA2Uk&list=PLa7VYi0yPIH2GTo3vRtX8w9tgNTTyYSux
Today’s businesses are increasingly software-defined, and their business processes are being automated. Whether it’s orders and shipments, or downloads and clicks, business events can always be streamed. Flink can be used to manipulate, process, and react to these streaming events as they occur.
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
高可用+
https://redis.io/blog/high-availability-architecture/
A high available architecture is when there are a number of different components, modules, or services that work together to maintain optimal performance, irrespective of peak-time loads.
https://www.ibm.com/think/topics/high-availability
High availability (HA) is a term that refers to a system’s ability to be accessible and reliable close to 100% of the time.
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
Hadoop+
https://www.runoob.com/w3cnote/hadoop-tutorial.html
Hadoop 为庞大的计算机集群提供可靠的、可伸缩的应用层计算和存储支持，它允许使用简单的编程模型跨计算机群集分布式处理大型数据集，并且支持在单台计算机到几千台计算机之间进行扩展。
[英文] Hadoop Tutorial
https://www.tutorialspoint.com/hadoop/index.htm
Hadoop is an open-source framework that allows to store and process big data in a distributed environment across clusters of computers using simple programming models.
HDFS+
https://hadoop.apache.org/docs/r1.2.1/hdfs_design.html
The Hadoop Distributed File System (HDFS) is a distributed file system designed to run on commodity hardware.
https://www.ibm.com/cn-zh/think/topics/hdfs
Hadoop 分布式文件系统 (HDFS) 是一种管理大型数据集的文件系统，可在商用硬件上运行。
MapReduce+
https://www.youtube.com/watch?v=bcjSe0xCHbE
https://www.youtube.com/watch?v=cHGaQz0E7AU
In this video I explain the basics of Map Reduce model, an important concept for any software engineer to be aware of.
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
HBase+
[英文] HBase Tutorial
https://www.tutorialspoint.com/hbase/index.htm
HBase is a data model that is similar to Google's big table designed to provide quick random access to huge amounts of structured data. This tutorial provides an introduction to HBase, the procedures to set up HBase on Hadoop File Systems, and ways to interact with HBase shell.
机器学习+
https://www.youtube.com/watch?v=0oyDqO8PjIg
Learn about machine learning and AI with this comprehensive 11-hour course from @LunarTech_ai.
https://www.youtube.com/watch?v=i_LwzRVP7bg
Learn Machine Learning in a way that is accessible to absolute beginners.
https://www.youtube.com/watch?v=NWONeJKn6kc
Learn the theory and practical application of machine learning concepts in this comprehensive course for beginners.
https://www.youtube.com/watch?v=PcbuKRNtCUc
Learn about all the most important concepts and terms related to machine learning and AI.
算法+
https://roadmap.sh/datastructures-and-algorithms
Step by step guide to learn Data Structures and Algorithms in 2025
https://www.hellointerview.com/learn/code
A visual guide to the most important patterns and approaches for the coding interview.
https://www.w3schools.com/dsa/
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