小鹏汽车【26校招】大数据开发工程师
校招全职地点：广州状态：招聘
任职要求
必需项： - 掌握SQL与至少一种编程语言（Python/Java/Scala）； - 理解数据库基本原理（索引/事务/数据分区）； - 熟悉Linux开发环境与脚本编写； - 理解机器学习基本概念（监督学习/表征学习/评估指标）。 加分项： - 了解Hadoop生态，包括Hadoop、Hive、Spark、ES、Kafka、Doris、Flink等； - 有数据仓库建模或ETL开发项目经验（课设/实习/竞赛）； - 熟悉列式存储（Parquet/ORC）或MPP数据库； - 了解向量数据库原理（近似最近邻/HNSW算法）； - 熟悉多模态表征学习（CLIP/BLIP等模型数据处理经验）； - 掌握深度学习框架生态（PyTorch分布式训练/TensorRT推理优化）； - 有LangChain/LLamaIndex等AI编排工具实践者优先； - 对自动驾驶数据特性有认知者优先。
工作职责
1. 自动驾驶数据建模 - 设计多源异构数据的数仓分层模型（ODS/DWD/DWS/ADS），支撑感知、预测等算法训练； - 设计支持相似性检索的数仓分层（ADS层集成VectorDB特性）； - 构建数据血缘与元数据管理体系，保障数据可追溯性； - 构建多模态数据的统一向量化标准（图像/点云/文本的Embedding规范）。 2. 大规模数据处理开发 - 开发高可靠ETL流程，处理车载传感器原始数据（摄像头/LiDAR/GPS等）； - 基于Spark/Flink优化数据清洗、转换、聚合任务，提升云端处理效能； - 开发多模态Embedding流水线（CV/NLP模型的分布式特征提取）； - 基于VLM（视觉语言模型）自动生成数据标签（替代人工标注）； - 构建驾驶场景语义索引系统（支持“极端天气”“危险变道”等语义检索）。 3. 分析平台建设 - 搭建数据湖仓一体架构（Paimon/Iceberg + Doris/StarRocks）； - 搭建海量特征向量数据库（Milvus/Pinecone/自研引擎）； - 开发BI可视化看板，监控数据质量及自动驾驶关键指标（生产折损率，感知准确率、干预率等）； - 开发多模态检索接口（如根据文本描述搜索关联驾驶场景视频）。 4. 效率优化 - 持续优化数据存储成本与计算性能（分区策略/压缩算法/计算资源调度）； - 探索弹性伸缩，流批一体，存算分离等架构在实时数据处理场景的应用。
包括英文材料
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.
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.
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.
Scala+
Linux+
https://ryanstutorials.net/linuxtutorial/
Ok, so you want to learn how to use the Bash command line interface (terminal) on Unix/Linux.
https://ubuntu.com/tutorials/command-line-for-beginners
The Linux command line is a text interface to your computer.
https://www.youtube.com/watch?v=6WatcfENsOU
In this Linux crash course, you will learn the fundamental skills and tools you need to become a proficient Linux system administrator.
https://www.youtube.com/watch?v=v392lEyM29A
Never fear the command line again, make it fear you.
https://www.youtube.com/watch?v=ZtqBQ68cfJc
脚本+
[英文] Scripting language
https://en.wikipedia.org/wiki/Scripting_language
https://zhuanlan.zhihu.com/p/571097954
一个脚本通常是解释执行而非编译。脚本语言通常都有简单、易学、易用的特性，目的就是希望能让程序员快速完成程序的编写工作。
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.
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
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.
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.
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.
Doris+
https://doris.apache.org/docs/gettingStarted/what-is-apache-doris
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.
Parquet+
https://www.youtube.com/watch?v=KLFadWdomyI
Learn all about Apache Parquet, a column-based file format that's popular in the Hadoop/Spark ecosystem.
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/
深度学习+
https://d2l.ai/
Interactive deep learning book with code, math, and discussions.
PyTorch+
https://datawhalechina.github.io/thorough-pytorch/
PyTorch是利用深度学习进行数据科学研究的重要工具，在灵活性、可读性和性能上都具备相当的优势，近年来已成为学术界实现深度学习算法最常用的框架。
https://www.youtube.com/watch?v=V_xro1bcAuA
Learn PyTorch for deep learning in this comprehensive course for beginners. PyTorch is a machine learning framework written in Python.
TensorRT+
https://docs.nvidia.com/deeplearning/tensorrt/latest/getting-started/quick-start-guide.html
This TensorRT Quick Start Guide is a starting point for developers who want to try out the TensorRT SDK; specifically, it demonstrates how to quickly construct an application to run inference on a TensorRT engine.
LangChain+
https://python.langchain.com/docs/tutorials/
New to LangChain or LLM app development in general? Read this material to quickly get up and running building your first applications.
https://www.freecodecamp.org/news/beginners-guide-to-langchain/
LangChain is a popular framework for creating LLM-powered apps.
LlamaIndex+
https://developers.llamaindex.ai/python/framework/getting_started/starter_example/
This tutorial will show you how to get started building agents with LlamaIndex.
https://www.ibm.com/think/tutorials/llamaindex-rag
LlamaIndex is a powerful open source framework that simplifies the process of building RAG pipelines.
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.
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