拜耳
Senior Data Engineer
Senior Data Engineer
发布于 大约 16 小时前普通员工/个人贡献者
ChinaChina
高级经验
全职员工
仅现场办公
本科
SQL
RAG
PySpark
ETL/ELT
AI 估算 · 30k–50k
高级数据工程师，外企平台，技能要求高，薪资竞争力强
职位详情
关于这个职位
作为高级数据工程师，你将在拜耳中国产品供应组织内，负责构建和维护可靠的数据管道，与全球团队协作，推动数据驱动的决策
你将参与前沿技术如RAG和Lakehouse的应用，并指导初级工程师
最低要求
Bachelor's degree in Computer Science, Data Science, Information Technology, or a related field
+ years of experience in data engineering, data operations, or a similar role, delivering production-grade data pipelines and services
Strong ownership of deliverables, high standards for code review and peer mentorship, and a commitment to clear documentation, metadata and lineage publishing, and sustainable data engineering standards and practices
Excellent analytical and problem-solving skills
Understanding of requirements related to product supply and manufacturing in the pharmaceutical industry
Good communication and collaboration abilities to work independently in a self-organized team
Fluent in Chinese and English
Willingness and ability to learn and integrate new tools and technologies to enhance work efficiency and effectiveness
Understanding of Data Product concepts and lifecycle management, including data quality key dimensions and tools such as Great Expectations, dbt tests, or Elementary
Hands-on experience building Retrieval-Augmented Generation (RAG) data pipelines, including automated document ingestion, preprocessing, chunking, embedding generation, and loading data into vector stores for efficient retrieval
Familiarity with RAG architectures and components such as vector databases, embedding models, and LLMs; experience designing these systems is a plus
Hands-on proficiency in SQL, Python, PySpark, or Spark to build scalable data pipelines using modern data processing frameworks such as Databricks or Snowflake
Proven experience with ETL/ELT tools such as Kettle/Pentaho, DataWorks, or similar
Ability to integrate data from source systems using interface patterns such as ODBC, GraphQL, OData, REST, or event streaming
Experience with cost and performance optimization and FinOps practices for cloud data platforms such as Snowflake or Databricks, ensuring reliable production operations
Understanding of modern lakehouse table formats such as Apache Iceberg and Delta Lake, and ability to design, build, maintain and document conceptual, logical and physical data models
Understanding of data architecture patterns such as data hub, data mesh, or data fabric
Experience with GxP and computerized system validation is a plus
工作职责
Work in an agile team and collaborate with colleagues all over the world to develop and operate reliable data pipelines from source to product to ensure compliant access and use of data related to the local Product Supply organization
Collaborate closely with relevant stakeholders in China and beyond to capture data-related business requirements and translate them into efficient technical solutions to ensure a fit-for-purpose technical implementation
Work with architects and subject matter experts to capture and manage dependencies between data solutions to ensure a healthy data ecosystem
Actively exchange with peers on best-practices, technical patterns and solutions and apply them in the local context to build and maintain a consolidated and scalable data landscape for the Product Supply organization in China
Mentor junior engineers and uphold high standards in code review, testing, and documentation of the implemented data solutions in China
优先资格
Familiarity with RAG architectures and components such as vector databases, embedding models, and LLMs; experience designing these systems is a plus
Experience with GxP and computerized system validation is a plus
AI 洞察
优缺点分析
- 拜耳作为跨国药企，提供稳定的平台和国际化工作环境
- 职位涉及前沿技术（RAG、Lakehouse、Data Mesh），有助于提升技术竞争力
- 与全球团队合作，积累跨文化协作经验
- 专注于制药行业数据，行业壁垒高，职业价值稳定
- 制药行业对数据合规性和验证要求高（如GxP），工作严谨度要求较高
- 涉及多种技术栈和工具，需要持续学习和适应
- 作为高级工程师，需同时承担代码审查和指导初级成员的责任
- 适合具备5年以上数据工程经验、渴望接触前沿技术、希望在稳定外企中深化行业知识的技术型人才
角色解读
- 技术路径：从高级工程师向数据架构师或数据科学家发展
- 管理路径：通过指导团队和承担更多项目职责，向数据工程经理或产品负责人转型
- 行业深耕：在制药行业数据领域成为专家，推动数据驱动的供应链优化
- 设计、开发和维护可靠的数据管道，确保从数据源到产品的合规数据访问和使用
- 与全球团队协作，将业务需求转化为高效的技术解决方案
- 管理数据依赖关系，维护健康的数据生态系统
- 使用现代数据处理框架（如Databricks、Snowflake）构建可扩展的数据管道
- 精通SQL、Python、PySpark或Spark等编程语言
- 熟悉ETL/ELT工具（如Kettle、DataWorks）和数据集成模式（ODBC、GraphQL、REST等）
- 掌握数据产品概念，包括数据质量工具（Great Expectations、dbt）
- 具备RAG管道构建经验，了解向量数据库、嵌入模型和LLM
申请策略
- 研究拜耳的产品供应组织架构，了解其业务痛点和数据需求
- 在面试中强调跨团队协作和业务理解能力
- 突出数据管道构建经验，尤其是生产级系统的设计和优化案例
- 强调使用Databricks、Snowflake等现代数据平台的实际项目
- 展示RAG或大模型相关项目经验，即使只是学习项目也有加分
- 提及在制药或严格合规行业的经验（如GxP）
- 学习RAG架构和向量数据库（如Pinecone、Weaviate）
- 熟悉云数据平台的成本优化（FinOps）和性能调优
面试指南
- STAR法则：描述情境、任务、行动和结果，强调量化成果
- 技术对比：指出技术选型的利弊，展示决策能力
- 最佳实践：结合行业标准（如GxP）说明你的方法
- 请描述你设计过的一个复杂数据管道，包括技术选型和遇到的挑战
- 你如何确保数据质量？使用过哪些工具和框架？
- 解释什么是RAG，你如何构建一个RAG管道？
- 在制药行业，数据合规性有哪些要求？你如何处理？
- 如何优化Databricks或Snowflake上的查询性能和成本？
匹配度报告
70
综合匹配度
外企高级数据工程师，前沿技术栈，发展空间大，WLB待确认
适合人群
适合重视技术成长和行业深耕的求职者，对WLB要求不是特别苛刻
最强匹配
成长发展匹配
最弱匹配
工作生活匹配
薪资福利70
成长发展85
工作生活60
使命价值65
薪资福利匹配
70中等
薪资水平未明确披露，但外企通常提供有竞争力的薪酬和福利；福利未在JD中提及，整体补偿性中等偏上。
薪资信号未披露 (30K-50K/月)
成长发展匹配
85较高
职位涉及RAG、Lakehouse、Data Mesh等前沿技术，能显著提升技能；有指导机会但未明确晋升路径，发展性较好。
技术前沿前沿/新兴技术
技术栈SQL、Python、PySpark、Spark、Databricks、Snowflake、RAG、Apache Iceberg、Delta Lake、Data Mesh
业务类型ambiguous
工作生活匹配
60中等
工作模式未明确，地点未知，但外企通常有较好WLB；JD未提及弹性办公或远程，生活化满足程度一般。
工作模式未明确
办公地点未明确
加班情况未提及（无法判断）
使命价值匹配
65中等
制药行业稳定但非高速增长，社会影响力正向但未强调，技术创新积极，意义感中等。
行业发展稳定成熟行业
社会影响中性/一般
创新程度积极采用新技术
Watch Jobs