高级数据工程师 - AI与分析

• 高级数据工程师 - AI与分析
• Description -
• 职位概述
• 我们正在寻找一名积极主动、经验丰富的高级数据工程师 - AI与分析，加入工厂数字化转型与人工智能团队。该岗位将重点建设并扩展企业级数据平台、分析解决方案及AI就绪的数据基础，为制造运营、质量提升、供应链可视化和下一代AI应用提供支撑。
• 理想候选人应具备扎实的数据工程、大规模分析平台和现代数据架构经验，并有意愿将人工智能与生成式AI技术应用于真实业务场景。
• 主要职责
• 企业级数据平台开发

• 设计、构建并维护可扩展的企业级数据平台，为制造分析和AI工作负载提供支持。
• 开发并优化来自多类数据源的批处理与流处理数据管道。
• 建设面向大规模分析环境的数据采集、处理、转换和服务层。
• 构建可复用、易维护、可用于生产环境的数据工程框架。

数据工程与分析

• 使用现代数据工程技术设计并实施可靠的ETL/ELT数据管道。
• 开发支持报表、自助分析、语义模型和AI应用的稳健数据模型。
• 优化数据处理的性能、可靠性、可扩展性和成本。
• 推动平台的数据质量、数据治理、血缘追踪和可观测性建设。

AI与生成式AI赋能

• 构建AI就绪的数据集和企业知识库。
• 开发支持检索增强生成（RAG）和企业AI应用的数据管道。
• 将大语言模型服务和语义搜索能力集成到业务工作流。
• 与AI工程师和数据科学家合作，推动AI解决方案和智能Agent的工程化落地。

制造分析

• 与工厂运营、工程和业务团队合作，解决以数据驱动的业务问题。
• 建设良率分析、工厂KPI平台、制造智能、测试数据分析、质量分析及供应链分析方案。
• 将业务需求转化为安全、可扩展、可维护的技术解决方案。

平台创新

• 评估大数据、云平台、分析及AI领域的新兴技术。
• 提出架构改进建议，并参与技术路线图规划。
• 推动软件工程、数据工程和平台开发的最佳实践。

• 任职资格
• 教育背景

• 计算机科学、数据工程、信息系统、软件工程或相关技术专业本科及以上学历。

工作经验

• 5年以上数据工程、大数据平台开发或分析工程相关经验。
• 具备企业级数据平台及生产数据管道的设计和建设经验。
• 具备大规模结构化与非结构化数据处理经验。
• 具备支持生产关键业务应用的经验。

技术能力

• 熟练掌握以下多项技术：Apache Spark、Apache Flink、Hive、Kafka、Airflow、Trino/Presto、Apache Iceberg或湖仓一体架构。
• 具备扎实的Python和SQL编程能力，包括SQL开发与性能优化。
• 熟悉关系型数据库、NoSQL及数据湖技术，例如SQL Server、PostgreSQL、MySQL、MongoDB或同类平台。
• 具备至少一种云平台经验：Microsoft Azure、AWS或Google Cloud Platform。
• 具备Git、CI/CD、Docker和Kubernetes使用经验者优先。

• 优先条件
• AI / 生成式AI

• 具备RAG、大语言模型应用、Agent框架、语义搜索或向量数据库经验。
• 熟悉LangChain、Azure AI服务、Azure AI Search或同类技术。

制造业经验

• 具备制造系统、工厂分析、MES、产品质量分析、测试工程数据平台或工业物联网解决方案经验。
• 理解制造数据、运营KPI及跨职能工厂业务流程。

核心能力

• 具备较强的问题分析与解决能力。
• 具备清晰的沟通表达和利益相关者管理能力。
• 能够在全球化、跨职能团队中有效协作。
• 自我驱动，具有主人翁意识、执行力和责任感。
• 持续学习，并对新兴技术保持好奇心。

你将参与建设

• 企业级AI平台与工厂AI助手
• 制造知识系统与基于RAG的搜索平台
• 工厂数据湖仓、分析与报表解决方案
• AI就绪的数据产品与语义模型
• 智能自动化工作流与数字化转型能力

Job Summary

We are seeking a highly motivated and experienced Senior Data Engineer - AI & Analytics to join our Factory Digital Transformation and AI team. This role focuses on building and scaling enterprise data platforms, analytics solutions, and AI-ready data foundations that support manufacturing operations, quality improvement, supply chain visibility, and next-generation AI initiatives.

The ideal candidate has strong expertise in data engineering, large-scale analytics platforms, and modern data architectures, together with a passion for applying AI and Generative AI technologies to real-world business challenges.

Key Responsibilities

Enterprise Data Platform Development

• Design, build, and maintain scalable enterprise data platforms supporting manufacturing analytics and AI workloads.
• Develop and optimize batch and streaming data pipelines across multiple data sources.
• Implement data ingestion, processing, transformation, and serving layers for large-scale analytics environments.
• Build reusable, maintainable, and production-ready data engineering frameworks.

Data Engineering & Analytics

• Design and implement reliable ETL/ELT pipelines using modern data engineering technologies.
• Develop robust data models for reporting, self-service analytics, semantic models, and AI applications.
• Optimize data processing performance, reliability, scalability, and cost.
• Promote data quality, governance, lineage, and observability across the platform.

AI & Generative AI Enablement

• Build AI-ready datasets and enterprise knowledge repositories.
• Develop data pipelines supporting Retrieval-Augmented Generation (RAG) and enterprise AI applications.
• Integrate LLM services and semantic search capabilities into business workflows.
• Collaborate with AI engineers and data scientists to operationalize AI solutions and intelligent agents.

Manufacturing Analytics

• Partner with factory operations, engineering, and business teams to solve data-driven challenges.
• Build solutions for yield analytics, factory KPI platforms, manufacturing intelligence, test data analytics, quality analytics, and supply chain analytics.
• Translate business needs into secure, scalable, and maintainable technical solutions.

Platform Innovation

• Evaluate emerging technologies in big data, cloud platforms, analytics, and AI.
• Recommend architectural improvements and contribute to technology roadmaps.
• Drive engineering best practices across software, data, and platform development.

Required Qualifications

Education

• Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, Software Engineering, or a related technical field.

Experience

• 5+ years of experience in data engineering, big data platform development, or analytics engineering.
• Proven experience building enterprise-scale data platforms and production data pipelines.
• Experience working with structured and unstructured data at scale.
• Experience supporting production-critical business applications.

Technical Skills

• Strong expertise in several of the following: Apache Spark, Apache Flink, Hive, Kafka, Airflow, Trino/Presto, Apache Iceberg, or lakehouse architecture.
• Strong programming skills in Python and SQL, including SQL development and performance optimization.
• Experience with relational, NoSQL, and data lake technologies such as SQL Server, PostgreSQL, MySQL, MongoDB, or equivalent platforms.
• Experience with at least one cloud platform: Microsoft Azure, AWS, or Google Cloud Platform.
• Working knowledge of Git, CI/CD, Docker, and Kubernetes is preferred.

Preferred Qualifications

AI / Generative AI

• Experience with RAG, LLM applications, agent frameworks, semantic search, or vector databases.
• Familiarity with LangChain, Azure AI services, Azure AI Search, or comparable technologies.

Manufacturing Industry

• Experience supporting manufacturing systems, factory analytics, MES, product quality analytics, test engineering data platforms, or Industrial IoT solutions.
• Understanding of manufacturing data, operational KPIs, and cross-functional factory workflows.

Core Competencies

• Strong problem-solving and analytical thinking.
• Clear communication and effective stakeholder management.
• Ability to work in global, cross-functional teams.
• Self-driven execution, ownership, and accountability.
• Continuous learning and curiosity about emerging technologies.

What You'll Build

• Enterprise AI platforms and factory AI assistants
• Manufacturing knowledge systems and RAG-based search platforms
• Factory data lakehouse, analytics, and reporting solutions
• AI-ready data products and semantic models
• Intelligent automation workflows and digital transformation capabilities

Job -

Data & Information Technology

• Schedule -
• Full time
• Shift -

First Shift (China)

Travel -

Relocation -

Equal Opportunity Employer (EEO) -

HP, Inc. provides equal employment opportunity to all employees and prospective employees, without regard to race, color, religion, sex, national origin, ancestry, citizenship, sexual orientation, age, disability, or status as a protected veteran, marital status, familial status, physical or mental disability, medical condition, pregnancy, genetic predisposition or carrier status, uniformed service status, political affiliation or any other characteristic protected by applicable national, federal, state, and local law(s).

Please be assured that you will not be subject to any adverse treatment if you choose to disclose the information requested. This information is provided voluntarily. The information obtained will be kept in strict confidence.

For more information, review HP’s EEO Policy or read about your rights as an applicant under the law here: “ Know Your Rights: Workplace Discrimination is Illegal "