1.
Work closely with Product Managers, Data Scientists/Analysts, and Software/Machine Learning Engineers and other stakeholders to understand data requirements and deliver data solutions that meet business needs.
2.
Evaluate, implement and maintain data infrastructure tools and technologies to support efficient data processing, storage and query.
3.
Design, build and optimize scalable data pipelines to ingest, process and transform large volumes of data.
4.
Design and implement robust data models and visualization to support complex analytical queries and reporting requirements.
5.
Ensure the data integrity, accuracy and consistency of data by implementing data quality checks, validation processes and monitoring mechanisms.
6.
Continously optimize data pipelines, queries and processes to improve performance, reduce latency and enhance scalability.
7.
Provide rapid response to SLA oncall support to business critical data pipelines.
8.
Create and maintain good documentation for data assets and promote best practices for data governance within the data user

系统翻译：
1.
与产品经理、数据科学家/分析师、软件/机器学习工程师和其他利益相关者密切合作，了解数据需求并提供满足业务需求的数据解决方案。
2.
评估、实施和维护数据基础设施工具和技术，以支持高效的数据处理、存储和查询。
3.
设计、构建和优化可扩展的数据管道，以摄取、处理和转换大量数据。
4.
设计和实施强大的数据模型和可视化，以支持复杂的分析查询和报告要求。
5.
通过实施数据质量检查、验证流程和监控机制，确保数据的完整性、准确性和一致性。
6.
持续优化数据管道、查询和流程，以提高性能、减少延迟并增强可扩展性。
7.
为业务关键数据管道的 SLA 待命支持提供快速响应。
8.
创建和维护良好的数据资产文档，并在数据用户中推广数据治理的最佳实践