饿了么饿了么-数据研发专家-北京/杭州
社招全职5年以上技术类-数据地点：北京 | 杭州状态：招聘
任职要求
1、从事数据仓库领域2年以上，熟悉仓库模型设计与ETL开发经验，有O2O领域数据建设经验优先； 2、掌握Kimball的维度建模设计方法，具备海量数据加工处理（ETL）相关经验，灵活运用SQL实现海量数据ETL加工处理，具备良好的SQL性能调优能力； 3、熟悉Hadoop生态相关技术并有相关实践经验，重点考察Hdfs、Mapreduce、Hive、Hbase、Spark； 4、熟悉数据仓库领域知识和技能者优先，包括但不局限于：数据集市设计、元数据管理、数据质量、主数据管理； 5、掌握实时流计算技术，有Flink开发经验者优先； 6、具备良好的数据分析和理解能力，能够将业务和数据连接，发掘机会，链接业务，解决问题； 7、良好的语言沟通与表达能力、较强的自我驱动能力。
工作职责
1、参与到本地生活PB级数据仓库的建设，通过构建本地生活零售数据中台，服务于本地生活商家和用户，提供丰富稳定的数据化产品服务 2、参与到本地生活用户、商品、商户等核心资产建设，构建丰富的人群标签库、商品库、商机库等，助力业务产品不断优化 3、能基于准确性、及时性、稳定性的要求不断提高数据中台的质量和服务
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.
SQL+
https://liaoxuefeng.com/books/sql/introduction/index.html
什么是SQL？简单地说，SQL就是访问和处理关系数据库的计算机标准语言。
https://sqlbolt.com/
Learn SQL with simple, interactive exercises.
https://www.youtube.com/watch?v=p3qvj9hO_Bo
In this video we will cover everything you need to know about SQL in only 60 minutes.
性能调优+
https://goperf.dev/
The Go App Optimization Guide is a series of in-depth, technical articles for developers who want to get more performance out of their Go code without relying on guesswork or cargo cult patterns.
https://web.dev/learn/performance
This course is designed for those new to web performance, a vital aspect of the user experience.
https://www.ibm.com/think/insights/application-performance-optimization
Application performance is not just a simple concern for most organizations; it’s a critical factor in their business’s success.
https://www.oreilly.com/library/view/optimizing-java/9781492039259/
Performance tuning is an experimental science, but that doesn’t mean engineers should resort to guesswork and folklore to get the job done.
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。
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.
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.
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.
数据分析+
[英文] Data Analyst Roadmap
https://roadmap.sh/data-analyst
Step by step guide to becoming an Data Analyst in 2025
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.
相关职位
社招3年以上技术-基础平台
1. 对接蚂蚁所有业务线的深度学习训练优化，开发分布式加速策略，定制算子，优化训练中数据预处理，低精度训练等模块，最终沉淀为通用解决方案并实现其自动化； 2. PyTorch/TensorFlow 等分布式训练内核优化扩展库研发； 3. 负责蚂蚁深度学习智能训练服务的研发； 4. 蚂蚁端到端的在线/离线学习训练系统开发。 5. 参与蚂蚁新一代分布式深度学习编译器开发 6. 参与蚂蚁开源深度学习系统DLRover开发建设
更新于 2025-10-17
社招5年以上云智能集团
1、负责并行文件系统的架构设计，设计并实现高性能、可扩展的并行文件系统架构。参与关键模块的研发，主导高效的目录树架构和数据路径性能可扩展架构。 2、负责稳定性架构，系统在高性能的同时，具备面向失败的设计，建设稳定性工程能力，构建可观测系统，夯实稳定安全能力。
更新于 2025-09-05
社招5年以上云智能集团
1. 负责阿里云容器产品管控系统的架构设计、功能开发和运维管理，打造稳定易用的容器服务管理平台。 2. 维护高性能、高可用的阿里云容器管控服务，保障业务系统在全球地域的稳定性。 3. 深入参与产品全生命周期研发管理，持续优化提升产品安全、稳定、性能、功能与用户体验，以技术驱动业务增长。 4. 推动系统架构演进及优化，关注前沿技术发展，完成技术预研和技术难点攻关。
更新于 2025-09-09
社招5年以上云智能集团
1.构建盘古分布式文件系统的标准化输出能力，提高系统的自动化部署、运维能力； 2.梳理盘古分布式文件系统管控系统的依赖，降低对外部系统的依赖，建立运维管控系统回归测试能力； 3.重构盘古管控系统的数据层和逻辑层，确保系统在迭代更新的过程中始终保证兼容性和服务稳定； 4.对接阿里云安全体系和基础管控系统，确保系统能在多用户环境下安全稳定运行。
更新于 2025-09-11