Data Engineer（数据开发工程师）

Role Overview:

We are building an AI Native team for a global trading product, aiming to rapidly validate and launch product modules through AI tools, data capabilities, and agile collaboration. This role will work closely with Product, Development, and Operations teams — responsible for data infrastructure, data analysis support, and BI visualization — helping the team gain faster insights into user behavior, product performance, and business opportunities.

Key Responsibilities:

1. Data Warehouse & Data Pipeline Development

- Participate in the design, development, and maintenance of the enterprise data warehouse

- Complete data ingestion, cleaning, transformation, and modeling from multiple sources

- Ensure data accuracy, completeness, and timeliness

2. Product & Business Data Analysis Support

- Structure data requirements around trading products, user behavior, growth conversion, content operations, and other scenarios

- Define core metrics and deliver actionable data analysis and business insights

3. BI Reporting & Dashboard Development

- Independently complete the full workflow — from data extraction and metric definition to report development and visualization dashboard creation

- Support business teams in daily monitoring and decision-making

4. Participation in AI Native Product Work

- Collaborate with Product, Development, and Operations to explore AI tool applications in data processing, automated analysis, report generation, and product validation

- Improve data development and business analysis efficiency

5. Data Quality & Data Governance

- Establish foundational data validation, anomaly monitoring, and metric definition management mechanisms

- Continuously optimize data quality and the overall data user experience

6. Cross-Team Collaboration & English Communication

- Collaborate with overseas teams, product teams, and technical teams

- Read English technical documentation and handle basic work communication, emails, and documentation in English

Required Qualifications:

1. Bachelor's degree or above — Computer Science, Data Science, Statistics, Information Management, Financial Engineering, or related fields preferred

2. 3+ years of experience in data engineering, BI development, or data warehousing — exceptional candidates with slightly less experience will be considered, with greater emphasis on learning ability, project experience, and tangible output

3. Proficient in SQL — capable of complex queries, data modeling, performance optimization, and troubleshooting

4. Proficient in Python or Java — for data processing, scripting, automation, ETL optimization, and related tasks

5. Familiar with at least one mainstream database or data platform — such as MySQL, PostgreSQL, Oracle, Hive, BigQuery, etc. — BigQuery experience preferred

6. Familiar with BI tools — such as Tableau, Power BI, FineBI, Looker Studio, etc. — able to independently develop dashboards and business reports

7. Strong business understanding — able to translate business problems into data metrics and analytical frameworks; willing to deeply understand trading products, FinTech, and global markets

8. Experience with AI tools preferred — such as ChatGPT, Claude, Cursor, Trae, Coze, DeepSeek, etc. — and able to apply them to code development, data analysis, automation, or efficiency improvement

9. English proficiency as a working language — able to read English technical documentation and handle basic emails, documentation, and cross-team communication in English

Preferred Qualifications:

1. Experience with FinTech, brokerages, trading platforms, market data, user growth, risk control, or payments-related data

2. Experience building data pipelines, metric systems, BI dashboards, or data platforms from 0 to 1

3. Practical experience using AI tools for data analysis, code generation, report automation, data cleaning, or business insight generation

4. Familiar with product development processes — willing to participate in product experiments, requirement discussions, and rapid iteration, rather than passively receiving data requests

What We're Looking For:

1. You are not just "a person who builds reports" — you are a data partner willing to solve problems together with Product, Development, and Operations teams

2. You stay curious about new tools — willing to use AI to improve your own efficiency, and open to experimentation and iteration in a fast-changing product environment

3. If you are interested in FinTech, trading products, AI tool implementation, and global markets — we'd love to have you on board

岗位描述：

我们正在组建一个面向全球交易产品的 AI Native团队，希望通过 AI 工具、数据能力和敏捷协作方式，快速验证和落地产品模块。该岗位将与产品、开发、运营紧密合作，负责数据基础建设、数据分析支持和 BI 可视化，帮助团队更快理解用户行为、产品表现和业务机会。

工作职责：

1. 负责数据仓库与数据链路建设

- 参与企业数据仓库的设计、开发和维护

- 完成多源数据的接入、清洗、转换和建模

- 保障数据准确性、完整性和时效性

2. 支持产品与业务数据分析

- 围绕交易产品、用户行为、增长转化、内容运营等场景，梳理数据需求

- 定义核心指标，输出可落地的数据分析和业务洞察

3. 负责 BI 报表和数据看板搭建

- 独立完成从数据提取、指标定义、报表开发到可视化看板搭建的全流程

- 支持业务团队日常监控和决策

4. 参与 AI Native 产品工作

- 与产品、开发、运营一起探索 AI 工具在数据处理、分析自动化、报表生成、产品验证中的应用

- 提升数据开发和业务分析效率

5. 推动数据质量和数据治理

- 建立基础的数据校验、异常监控和数据口径管理机制

- 持续优化数据质量和数据使用体验

6. 跨团队协作与英文沟通

- 与海外团队、产品团队和技术团队协作

- 能够阅读英文技术文档，并使用英语进行基础工作沟通、邮件和文档撰写

任职要求：

1. 本科及以上学历，计算机、数据科学、统计学、信息管理、金融工程等相关专业优先

2. 具备 3 年以上数据工程、BI开发或数据仓库相关经验；优秀候选人可适当放宽年限，更看重学习能力、项目经验和实际产出

3. 熟练使用 SQL，具备复杂数据查询、数据建模、性能优化和数据问题排查能力

4. 熟悉 Python 或 Java，能够用于数据处理、脚本开发、自动化任务、ETL 流程优化等工作

5. 熟悉至少一种主流数据库或数据平台，如 MySQL、PostgreSQL、Oracle、Hive、BigQuery 等；有 BigQuery 使用经验优先

6. 熟悉 BI 工具，如 Tableau、Power BI、FineBI、Looker Studio 等，能够独立完成数据看板和业务报表开发

7. 具备较好的业务理解能力，能将业务问题转化为数据指标和分析方案，愿意深入理解交易产品、金融科技和全球市场

8. 有 AI 工具使用经验优先，例如 ChatGPT、Claude、Cursor、Trae、Coze、DeepSeek 等，并能实际用于代码开发、数据分析、自动化或效率提升

9. 英语可作为工作语言，能够阅读英文技术文档，并完成基础英文邮件、文档和跨团队沟通

加分项：

1. 有金融科技、券商、交易平台、行情数据、用户增长、风控或支付相关数据经验

2. 有从 0 到 1 搭建数据链路、指标体系、BI 看板或数据平台的经验

3. 有使用 AI 工具完成数据分析、代码生成、报表自动化、数据清洗或业务洞察生成的实际案例

4. 熟悉产品开发流程，愿意参与产品实验、需求讨论和快速迭代，而不只是被动接数据需求

我们希望你是这样的人：

1. 你不只是一个"做报表的人"，而是一个愿意和产品、开发、运营一起解决问题的数据伙伴

2. 你需要对新工具保持好奇，愿意用 AI 提升自己的工作效率，也愿意在快速变化的产品环境里试错和迭代

3. 如果你对金融科技、交易产品、AI 工具落地和全球市场感兴趣，欢迎加入我们