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
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 …
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工作职责
1. 商业化与市场拓展 • 负责产品的商业化设计:定价策略、Package 组合、混合云 / 专有云 / 一体机多形态交付; • 构建产品 Go-to-Market 体系,包括定位、竞品分析、销售赋能材料、渠道与 ISV 合作。 • 联动销售、解决方案、生态合作伙伴推进重点客户项目(金融、能源、政务、运营商、央国企),贡献收入与标杆案例; • 参与 RFP / POC / 投标,主导产品相关商务方案与技术澄清,推动订单转化; 2. 产品规划与战略 • 负责 TBDS / WeData 产品线中一个或多个核心模块(数据湖仓 / 实时计算 / 数据开发 / 数据治理 / AI for Data)的产品规划与路线图设计; • 深入洞察大数据与 AI 行业趋势制定差异化产品策略; • 规划并落地 Data × AI 融合能力:NL2SQL、Agent 化数据开发、智能数据治理、向量 / 多模态湖仓、RAG 数据服务等; • 基于客户、市场、技术三方输入,输出年度 / 季度产品 Roadmap,并对关键业务指标(ARR、活跃客户数、Gross Margin)负责。 3. 需求与产品交付 • 对接客户与一线团队,沉淀行业需求,输出高质量 PRD / 交互稿,主导产品需求评审; • 与研发、设计、测试、运维紧密协作,把控版本节奏、上线质量与 SLA; • 持续跟进产品数据(使用量、留存、转化、NPS),基于数据驱动迭代。
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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