小鹏汽车大数据后端开发工程师 - 平台方向
社招全职地点:广州状态:招聘
任职要求
1. 本科及以上学历,计算机类相关专业,有不错的后端开发经验; 2. 优秀的编程和调试能力,精通至少一种主流编程语言, 如Java,Python,Go; 3. 熟悉大数据生态环境,掌握Hadoop,Hive,Kafka,Spark,Flink,Redis,ElasticSearch等大数据技术栈; 4. 对实时框驾有深入了解,在生产环境有TB级别Flink实时计算系统开发经验,深入掌握Flink DataStream、FlinkSQL、Flink Checkpoint、Flink State等模块,有Flink源码阅读经验优先; 5. 熟练使用MySQL/PostgreSQL/Redis/Kafka/Elasticsearch等常用存储技术,并熟悉其使用方式和实现原理; 6. 熟练使用doris/clickhouse/druid/presto/hbase等OLAP工具,并且掌握其原理; 7. 熟悉Paimon/Iceberg等数据湖技术的实时湖仓构建,ACID事务支持、增量更新和Time Travel查询,了解小文件合并和Schema演化等问题的解决 8. 有快速学习能力,能快速理解业务背景,善于沟通,主动性强,有责任心,具备优秀的技术与业务结合能力。 加分项: 9. 有数据质量、元数据管理等相关数据组件的实际经验 10. 熟悉基于StarRocks/Doris开发高性能OLAP查询,设计物化视图和分区分桶策略提升查询效率 11. 熟悉数据仓库各类模型建模理论,了解数据仓库数据分层架构、维度模型设计 12. 有基于Docker、Kubernetes、微服务的应用开发设计经验优先; 13. 有自动驾驶或大型互联网公司相关从业经验优先
工作职责
团队介绍: 小鹏汽车自动驾驶的大数据方向,负责所有自动驾驶数据的云端处理,为自动驾驶业务提供高性能,高质量的数据加工,保证整个数据生产的稳定性,及时性,高可用。 1. 负责自动驾驶大数据多模态(如视频、图像、雷达信号等)湖仓平台的架构设计、开发与建设,包括数据处理、资源调度、算子管理、部署服务等;负责数据采集、清洗、转换和加载(ETL)流程的开发,处理多源异构数据 2. 基于大数据多模态湖仓平台,协助客户处理生产业务中的海量数据,解决疑难问题,支持百亿级自动驾驶感知和全栈数据的快速定位和分析,赋能上层业务发展。 3. 协助设计和优化数据仓库模型,参与数据治理工作(如数据质量核查、元数据管理等) 4. 负责自动驾驶离线和实时数据仓库的构建和性能优化;负责车端信号数据仓库体系和数据指标体系的架构设计与开发,为算法和数据闭环提供框架支持; 5. 调优分布式计算引擎(Spark/Flink/Presto)及存储系统(HDFS/OSS),构建OLAP引擎(Doris/StarRocks),解决海量数据场景下的资源瓶颈。 6. 跟踪Iceberg、Paimon、Flink、Spark、Lance等开源技术演进,主导关键组件二次开发或源码级优化;负责前沿技术的跟踪研究,工具链的选型测试,解决、攻克数据平台的核心技术难题。 7. 建立监控和反馈指标,持续优化改进产品的架构及性能,保证PB级数仓的数据质量和平台稳定性。
包括英文材料
学历+
后端开发+
https://www.youtube.com/watch?v=tN6oJu2DqCM&list=PLWKjhJtqVAbn21gs5UnLhCQ82f923WCgM
Learn what technologies you should learn first to become a back end web developer.
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.
Python+
https://liaoxuefeng.com/books/python/introduction/index.html
中文,免费,零起点,完整示例,基于最新的Python 3版本。
https://www.learnpython.org/
a free interactive Python tutorial for people who want to learn Python, fast.
https://www.youtube.com/watch?v=K5KVEU3aaeQ
Master Python from scratch 🚀 No fluff—just clear, practical coding skills to kickstart your journey!
https://www.youtube.com/watch?v=rfscVS0vtbw
This course will give you a full introduction into all of the core concepts in python.
Go+
https://www.youtube.com/watch?v=8uiZC0l4Ajw
学习Golang的完整教程!从开始到结束不到一个小时,包括如何在Go中构建API的完整演示。没有多余的内容,只有你需要知道的知识。
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.
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
Kafka+
https://developer.confluent.io/what-is-apache-kafka/
https://www.youtube.com/watch?v=CU44hKLMg7k
https://www.youtube.com/watch?v=j4bqyAMMb7o&list=PLa7VYi0yPIH0KbnJQcMv5N9iW8HkZHztH
In this Apache Kafka fundamentals course, we introduce you to the basic Apache Kafka elements and APIs, as well as the broader Kafka ecosystem.
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.
Redis+
[英文] Developer Hub
https://redis.io/dev/
Get all the tutorials, learning paths, and more you need to start building—fast.
https://www.runoob.com/redis/redis-tutorial.html
REmote DIctionary Server(Redis) 是一个由 Salvatore Sanfilippo 写的 key-value 存储系统,是跨平台的非关系型数据库。
https://www.youtube.com/watch?v=jgpVdJB2sKQ
In this video I will be covering Redis in depth from how to install it, what commands you can use, all the way to how to use it in a real world project.
ElasticSearch+
https://www.youtube.com/watch?v=a4HBKEda_F8
Learn about Elasticsearch with this comprehensive course designed for beginners, featuring both theoretical concepts and hands-on applications using Python (though applicable to any programming language). The course is structured in two parts: first covering essential Elasticsearch fundamentals including index management, document storage, text analysis, pipeline creation, search functionality, and advanced features like semantic search and embeddings; followed by a practical section where you'll build a real-world website using Elasticsearch as a search engine, working with the Astronomy Picture of the Day (APOD) dataset to implement features such as data cleaning pipelines, tokenization, pagination, and aggregations.
MySQL+
https://juejin.cn/post/7190306988939542585
这是一篇 MySQL 通关一篇过硬核经验学习路线,包括数据库相关知识,SQL语句的使用,数据库约束,设计等。
[英文] MySQL Tutorial
https://www.mysqltutorial.org/
your go-to resource for mastering MySQL in a fast, easy, and enjoyable way.
https://www.youtube.com/watch?v=5OdVJbNCSso
MySQL SQL tutorial for beginners
https://www.youtube.com/watch?v=7S_tz1z_5bA
This beginner-friendly course teaches you SQL from scratch.
PostgreSQL+
[英文] PostgreSQL Tutorial
https://neon.com/postgresql/tutorial
This PostgreSQL tutorial helps you quickly understand PostgreSQL.
[英文] PostgreSQL Tutorial
https://www.pgtutorial.com/
This PostgreSQL tutorial will teach you about PostgreSQL from beginner to advanced.
https://www.youtube.com/watch?v=qw--VYLpxG4
It is the most advanced open source database system widely used to build back-end systems.
https://www.youtube.com/watch?v=SpfIwlAYaKk
Learn PostgreSQL, one of the world's most advanced and robust open-source relational database systems.
Doris+
https://doris.apache.org/docs/gettingStarted/what-is-apache-doris
ClickHouse+
[英文] Advanced Tutorial
https://clickhouse.com/docs/tutorial
Learn how to ingest and query data in ClickHouse using the New York City taxi example dataset.
https://www.youtube.com/watch?v=FtoWGT7kS-c
ClickHouse is an open-source column-oriented DBMS for online analytical processing that allows users to generate analytical reports using SQL queries in real-time.
https://www.youtube.com/watch?v=Rhe-kUyrFUE&list=PL0Z2YDlm0b3gcY5R_MUo4fT5bPqUQ66ep
Presto+
[英文] What is Presto?
https://prestodb.io/what-is-presto/
https://www.tutorialspoint.com/apache_presto/index.htm
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.
OLAP+
https://www.youtube.com/watch?v=iw-5kFzIdgY
OLAP (for online analytical processing) is software for performing multidimensional analysis at high speeds on large volumes of data from a data warehouse, data mart, or some other unified, centralized data store.
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.
StarRocks+
https://docs.starrocks.io/docs/quick_start/
These Quick Start guides will help you get going with a small StarRocks environment.
https://itnext.io/introduction-to-starrocks-a-new-modern-analytical-database-1db2177d26e1
Recently, I had the opportunity to explore StarRocks which is the new kid in the block when talking about massive scale databases which are able to handle petabytes of data.
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
Docker+
https://www.youtube.com/watch?v=GFgJkfScVNU
Master Docker in one course; learn about images and containers on Docker Hub, running multiple containers with Docker Compose, automating workflows with Docker Compose Watch, and much more. 🐳
https://www.youtube.com/watch?v=kTp5xUtcalw
Learn how to use Docker and Kubernetes in this complete hand-on course for beginners.
Kubernetes+
https://kubernetes.io/docs/tutorials/kubernetes-basics/
This tutorial provides a walkthrough of the basics of the Kubernetes cluster orchestration system.
https://kubernetes.io/zh-cn/docs/tutorials/kubernetes-basics/
本教程介绍 Kubernetes 集群编排系统的基础知识。每个模块包含关于 Kubernetes 主要特性和概念的一些背景信息,还包括一个在线教程供你学习。
https://www.youtube.com/watch?v=s_o8dwzRlu4
Hands-On Kubernetes Tutorial | Learn Kubernetes in 1 Hour - Kubernetes Course for Beginners
https://www.youtube.com/watch?v=X48VuDVv0do
Full Kubernetes Tutorial | Kubernetes Course | Hands-on course with a lot of demos
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.
自动驾驶+
https://www.youtube.com/watch?v=_q4WUxgwDeg&list=PL05umP7R6ij321zzKXK6XCQXAaaYjQbzr
Lecture: Self-Driving Cars (Prof. Andreas Geiger, University of Tübingen)
https://www.youtube.com/watch?v=NkI9ia2cLhc&list=PLB0Tybl0UNfYoJE7ZwsBQoDIG4YN9ptyY
You will learn to make a self-driving car simulation by implementing every component one by one. I will teach you how to implement the car driving mechanics, how to define the environment, how to simulate some sensors, how to detect collisions and how to make the car control itself using a neural network.
相关职位
社招3年以上A43408
1、负责设计、开发数据平台与后端服务的架构,确保系统在高并发、大数据场景下具备良好的可用性、高性能及扩展性,满足业务增长需求; 2、设计数据库规划存储方案,实现高效存储与快速检索,搭建后端服务,实现业务逻辑; 3、遵循微服务架构,拆分业务为独立模块,优化系统;协同前端团队,定义、维护API接口,保障数据交互流畅,提升用户体验。
更新于 2025-06-23
社招JMT32
1、负责字节跳动数据平台-流量平台后端开发和架构设计工作,支持公司二十万埋点和每日万亿数据处理; 2、负责数据产品架构设计和后端开发,设计和实现后端和关键数据服务; 3、负责数据产品的功能迭代和性能优化,提高效率,优化流程; 4、保障技术系统稳定可靠,熟练运用合适技术对复杂场景做出合理技术设计,保障和提升海量数据平台相关系统的性能和稳定性。
更新于 2021-08-24
校招研发技术类
1. 负责互联网基础架构(大数据、运维、安全等)相关效能平台的设计和开发工作,面向AI原生时代的基建效能平台开发,通过大模型技术重构传统运维、数据、安全体系,打造具备自进化能力的智能基础设施中台; 2. 智能平台开发:基于大模型开发AIOps工具,实现日志分析/故障预测自动化;构建Prompt工程框架,优化LLM在运维场景的落地效率; 3. DataOps体系建设:搭建自动化数据流水线,集成质量监控与版本控制功能;开发DataAgent实现自然语言交互式数据查询; 4. 安全架构优化:设计AI驱动的威胁感知系统,实现攻击模式预测;开发敏感数据自动识别与合规审计工具; 5. 云原生运维:优化K8s资源调度算法与智能扩缩容策略。
更新于 2025-10-14