腾讯腾讯云-TBDS大数据产品商业化负责人
社招全职5年以上腾讯云-大数据产品地点：深圳状态：招聘
工作描述
任职要求 1.本科及以上学历，计算机、软件工程、数据科学、人工智能、数学 / 统计等相关专业优先； 2.5 年以上 产品经理经验，其中 3 年以上 大数据 / 数据平台 / 数据库 / AI 平台类 To B 产品经验； 3.深度理解大数据技术栈：Hadoop 生态（HDFS / Hive / Spark / Flink）、湖仓一体（Iceberg / Hudi / Delta / Paimon）、OLAP（StarRocks / Doris / ClickHouse）、数据集成（CDC / Kafka）等； 4.熟悉 AI / 大模型相关产品形态：LLM 应用、RAG、Agent、向量数据库、MLOps / LLMOps 至少掌握其一； 5.具备较强的商业化能力：熟悉 To B SaaS / PaaS 产品的定价、Package、GTM 打法，或有过直接贡献收入 / ARR…
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包括英文材料
学历+
数据科学+
https://roadmap.sh/ai-data-scientist
Step by step roadmap guide to becoming an AI and Data Scientist
大数据+
https://www.youtube.com/watch?v=bAyrObl7TYE
https://www.youtube.com/watch?v=H4bf_uuMC-g
With all this talk of Big Data, we got Rebecca Tickle to explain just what makes data into Big Data.
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
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.
Iceberg+
https://iceberg.apache.org/spark-quickstart/
This guide will get you up and running with Apache Iceberg™ using Apache Spark™, including sample code to highlight some powerful features.
https://www.baeldung.com/apache-iceberg-intro
This tutorial will discuss Apache Iceberg, a popular open table format in today’s big data landscape.
https://www.youtube.com/watch?v=TsmhRZElPvM
You’ve probably heard about Apache Iceberg™—after all, it’s been getting a lot of buzz.
Hudi+
[英文] Spark Quick Start
https://hudi.apache.org/docs/quick-start-guide
we will walk through code snippets that allows you to insert, update, delete and query a Hudi table.
https://www.oreilly.com/library/view/apache-hudi-the/9781098173821/
Overcome challenges in building transactional guarantees on rapidly changing data by using Apache Hudi.
https://www.youtube.com/watch?v=pyK18sDYnS0
In this video, I'll introduce you to one of the most popular Data Lake solutions out there, Apache Hudi!
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