Data Engineer（数据工程师）

About Us / 关于我们:

Join our Digital Labs, a top-tier digital product team comprising passionate experts in AI, data science, engineering, and product development. Driven by a spirit of craftsmanship, we develop cutting-edge platforms and tools that accelerate innovation and solve complex real-world problems.

加入我们数字化实验室（Digital Labs），这里汇聚了人工智能、数据科学、工程技术和产品开发领域的顶尖人才。我们秉承匠心精神，致力于开发前沿平台和工具，加速创新，解决复杂的实际问题。

Role Description / 职位描述:

We are seeking a seasoned Data Engineer to join our core data team. In this role, you will be responsible for designing, building, and maintaining robust, scalable data infrastructure, pipelines, and products. You will ensure the efficient, reliable flow and governance of data, and deeply engage in the full lifecycle from data insight to production deployment, enabling data-driven decision-making and innovation across the organization.

我们正在寻找一位资深的数据工程师，加入我们的核心数据团队。在这个角色中，你将负责设计、构建和维护健壮、可扩展的数据基础设施、管道与产品。你需要确保数据的高效、可靠流动与治理，并深度参与从数据洞察到生产部署的全流程，赋能整个组织的数据驱动决策与创新。

Key Responsibilities / 核心职责:

1. Analyze complex business and technical requirements to design and implement tailored data architecture and engineering solutions.

分析复杂的业务与技术需求，设计与实施定制化的数据架构与工程解决方案。

2. Develop, deploy, and operate scalable, high-performance, and cost-efficient batch & streaming data pipelines, services, and platform components.

开发、部署并运维可扩展、高性能、高性价比的批流一体数据管道、服务及平台组件。

3. Collaborate with cross-functional teams to define data models, SLAs, and governance standards, translating needs into reliable products, services, or insights.

与跨职能团队紧密协作，共同定义数据模型、SLA及治理标准，将数据需求落地为可靠的产品、服务或洞察。

4. Maintain high standards for code quality, system scalability, security, and data governance in all engineering practices.

在工程实践中始终保持对代码质量、系统可扩展性、安全性与数据治理的高标准要求。

5. Stay updated on and evaluate cutting-edge data engineering technologies, tools, and best practices to drive technological evolution and efficiency gains within the team.

持续探索并评估前沿的数据工程技术、工具与最佳实践，推动团队技术演进与效率提升。

Specialization Tracks / 专业方向:

本职位提供两个重点发展路径，候选人将根据专长与团队需求侧重其一。This role offers two primary specialization tracks, and candidates will focus on one based on their expertise and team needs.

· Data Product Engineer / 数据产品工程师:

o Role Focus / 角色定位: Acts as the data product owner, leading the end-to-end delivery of data-driven analytical solutions.

作为数据产品负责人，主导数据驱动的分析解决方案从需求到交付的全流程。

o Core Focus / 核心焦点: Designs, builds, and maintains high-quality, reusable data assets and analytical products that directly empower business decisions and product features.

设计、构建并维护直接赋能业务决策与产品的高质量、可复用数据资产与分析产品。

o Key Responsibilities / 关键职责:

§ Takes ownership of business analysis and insights, including the design, development, and maintenance of key business dashboards, reports, and deep-dive analyses.

直接负责业务分析与洞察交付，包括设计、开发与维护关键业务数据看板、报表及深度分析。

§ Partners with data scientists to productize ML feature engineering, experimentation analysis, and data workflows, building reliable, monitored production-grade data pipelines.

与数据科学家合作，将机器学习特征工程、实验分析与数据工作流产品化，构建可靠、可监控的生产级数据管道。

§ Conducts data modeling, builds ETL/ELT pipelines with quality checks, and publishes governed core data assets via secure data services or APIs.

进行数据建模，构建具备质量监控的ETL/ELT管道，并通过安全的数据服务或API发布经过治理的核心数据资产。

· Cloud Data Platform Engineer / 云数据平台工程师:

o Role Focus / 角色定位: Acts as the core builder of the Internal Data Platform, serving as a force multiplier for all data practitioners.

作为内部数据平台的核心构建者，扮演“效能倍增器”的角色。

o Core Focus / 核心焦点: Designs and implements infrastructure, guardrails, and automation to enhance the productivity and experience of all data developers.

设计并实现基础设施、标准规范及自动化流程，提升所有数据开发者的生产效率与体验。

o Key Responsibilities / 关键职责:

§ Designs, builds, and maintains a scalable, secure, and highly available Internal Data Platform that provides an exceptional Developer Experience (DX).

设计、构建并维护可扩展、安全、高可用的内部数据平台，提供卓越的开发者体验。

§ Integrates cloud PaaS data services and develops quality control, governance frameworks, and bespoke services not covered out-of-the-box.

集成云PaaS数据服务，并开发平台原生功能未覆盖的质量控制、治理框架及定制化服务。

§ Productizes the developer "golden path" through self-service tools and automation; builds monitoring, alerting, and Policy-as-Code systems to ensure platform governance and observability.

产品化开发者的“黄金路径”，通过自服务工具和自动化消除研发摩擦；构建监控、告警及策略即代码系统以保障平台治理与可观测性。

Daily Work / 日常工作:

· Pipeline & Platform Development: Design, implement, and optimize batch and streaming data pipelines using modern frameworks (e.g., Spark, Flink, Kafka).

管道与平台开发：使用现代框架（如Spark, Flink, Kafka）设计、实现和优化批处理与流式数据管道。

· Data Modeling & Governance: Design and implement efficient data models (dimensional, normalized, data vault) and enforce data quality, security, and governance standards across the data lifecycle.

数据建模与治理：设计并实施高效的数据模型（维度、范式、Data Vault），并在数据全生命周期中执行数据质量、安全和治理标准。

· Cloud Infrastructure Management: Build, manage, and optimize data infrastructure on cloud platforms (AWS, Azure, GCP), leveraging services like data warehouses, data lakes, and serverless computing.

云基础设施管理：在云平台（AWS, Azure, GCP）上构建、管理和优化数据基础设施，熟练运用数据仓库、数据湖和无服务器计算等服务。

· Cross-functional Collaboration: Work closely with data scientists, analysts, and business stakeholders to understand requirements, deliver data solutions, and support data-driven initiatives.

跨职能协作：与数据科学家、分析师和业务利益相关者紧密合作，理解需求，交付数据解决方案，并支持数据驱动项目。

· Operational Excellence: Ensure the reliability, performance, and cost-efficiency of data systems through monitoring, alerting, troubleshooting, and continuous improvement.

卓越运维：通过监控、告警、故障排查和持续改进，确保数据系统的可靠性、性能与成本效益。

Key Qualifications / 任职要求:

· Master’s degree or higher in Computer Science, Engineering, or a related field.

计算机科学、工程或相关领域的硕士及以上学历。

· At least 5+ years of hands-on experience in data engineering, analytics platforms, or related fields.

至少5年以上数据工程、数据分析平台或相关领域的实践经验。

· Strong foundation in data structures, algorithms, and distributed system design.

扎实的数据结构、算法和分布式系统设计基础。

· Excellent communication and teamwork skills, with a proactive problem-solving attitude.

优秀的沟通与团队协作能力，以及积极主动解决问题的态度。

· Proficiency in Mandarin and English is preferred.

优秀的中文和英文沟通能力者优先。

Technical Expertise / 技术专长:

· Proficiency in at least one programming language such as Python, Java, Scala, or Go, and expert-level SQL skills.

精通Python、Java、Scala或Go中的至少一门编程语言，并拥有专家级SQL能力。

· Advanced knowledge of big data technologies and frameworks (e.g., Spark, Flink, Kafka, Airflow/Dagster).

深入理解大数据技术与框架（如Spark, Flink, Kafka, Airflow/Dagster）。

· Extensive experience in database design, optimization, and working with diverse data stores (Relational, NoSQL, Lakehouse Table Formats).

在数据库设计、优化及使用多种数据存储（关系型、NoSQL、数据湖表格式）方面拥有丰富经验。

· Hands-on experience with major cloud platforms (AWS, Azure, GCP) and their data services.

具备主流云平台（如AWS, Azure, GCP）及相关数据服务的实战经验。

Additional Expertise / 附加专长 (Preferred Qualifications):

· For Data Product Engineer Track / 数据产品工程师方向:

o Experience building and maintaining large-scale data warehouses, data lakes, and end-to-end data products; proven success in delivering business analysis insights.

拥有构建和维护大规模数据仓库、数据湖及端到端数据产品的经验；具备直接交付业务分析洞察的成功案例。

· For Cloud Platform Engineer Track / 云数据平台工程师方向:

o Experience with Docker/K8s in production, Infrastructure as Code (e.g., Terraform), CI/CD pipelines, and developer tooling.

具备Docker/Kubernetes生产环境经验、Terraform等IaC工具经验、CI/CD及开发者工具链建设经验。

· General / 通用要求:

o Proven track record of shipping and operating multiple data products or platform components that serve cross-functional teams and meet stringent SLAs.

拥有成功交付并运维多个服务多团队、满足严格SLA要求的数据产品或平台组件的经验。

o Relevant cloud data engineer or architect certifications are a plus.

拥有相关云服务商的数据工程师或架构师认证者更佳。