主要数据工程师-DATA产品建设

The Principal Data Engineer in the area of Data Engineering is a pivotal role in the Enterprise Data Engineering & Analytics Department in operationalizing critical data engineering and analytics initiatives for MD Anderson’s digital business initiatives. The Principal Data Engineer manages, plans, builds and optimizes end-to-end solution delivery, data pipelines within the Context Engine, as well as partners with other Enterprise Data Engineering & Analytics teams to manage & build analytics deliverables for production use by our key data and analytics consumers.

主要数据工程师还管理并协调遵守数据治理过程和数据安全要求，同时创建，改进和操作这些集成和可重复使用的数据管道。这会导致更快的数据访问，集成的数据重复使用以及MD Anderson数据和分析计划的时间大大改善。

The Principal Data Engineer role requires working creatively and collaboratively with IS and Institutional leaders across the enterprise. It involves evangelizing effective data management practices and promoting better understanding of data and analytics. The Principal Data Engineer- Data Engineering partners closely with teams across MD Anderson, including Enterprise Development & Integration and Enterprise Data Science departments in the build out and delivery of data pipelines and analytics through the Context Engine Framework.

数据工程 - 端到端解决方案交付：
1.线索/交流/参与端到端解决方案交付，以提高信息功能并实现整个机构的数据价值。端到端的解决方案包括通过数据摄入，入口，出口，策展，管道构建，数据转换和建模步骤集成数据治理过程，从而在上下文引擎框架上构建了数据源和工具。合并高度集成的数据治理过程，这些过程始终跟踪数据出处，安全性，数据质量和本体论以及数据可视化和见解。
2. Lead/Communicate/Participate in the planning, architecture, analysis, design and build of end-to-end data pipelines & solutions in partnership with IS, Data Offices, Data Governance teams, other partners for efficient end-to-end management of MD Anderson data across the Context Engine.
3.线索/通信/参与现有的端到端数据管道和解决方案，这些数据管道和解决方案由一系列阶段组成，例如，数据流（例如，从数据源或获取的端点到集成到集成到特定用例的消耗））
4.领导和合并可重复的解决方案设计和数据模型，建立数据策划管道，包括分析，规格创建，清洁，转换，标准化，掌握，协调，验证，汇总数据和监视数据质量，并在我们的上下文引擎中监视数据质量。
5. Lead/Communicate/Participate and incorporate data governance and metadata management processes into the data ingestion, curation and pipeline building efforts.
6.探索和推广创新和现代工具，技术和架构，以部分或完全自动化最常见，可重复和乏味的数据准备和集成任务，以最大程度地减少手动和错误的流程并提高生产率

Standards, Testing & System Maintenance:

1。Manage, coordinate and adhere to standard operating procedures set by IS division as well as all MDA policies and maintain build standards (data steward / governance oversight sign off) for support of MDA Institutional data strategy including Context Engine.
2.根据需要管理文档准备，以实施增强或新技术
3.管理并遵循记录的变更控制过程，并可能执行更改控制审核
4。Manage & perform quality control and testing, and review the build of other analysts to ensure that solutions are technically sound
5.监督分析系统更新/分配模块的新版本
6.管理和执行对系统和流程的监管要求，质量标准和最佳实践的遵守，并与内部和外部利益相关者合作
7. Lead and/or participate in after-hours application support and downtime procedures

教育和火车：

1。Lead, promote & train counterparts, such as data scientists, data analysts, users or any data consumers, in data pipelining and preparation techniques, which make it easier for them to integrate and consume the data they need for their own use cases.
2.在上下文引擎工具套件中为各种系统的领导，计划和制定培训计划，并与MDA培训团队和EDEA系统专家合作开发课程。
3.提供EDEA可交付成果的机构，部门和一对一培训
4。Coach and provide advice, guidance, encouragement, constructive feedback and transfer knowledge to less experienced team members across OneIS and the institution
5.管理与客户和Onis的联络关系，以提供有效的技术解决方案和客户服务

onis：

1.提供创新，质量和可持续的IT解决方案和服务。我们的成功是由我们的人民通过诚信和信任，伙伴关系和质量驱动的。
2.促进信任，尊重，支持和诚实与客户和彼此之间。
3. Commit to being a good partner focused on building productive, collaborative, and trusting relationships with our customers and each other.
4.建模对卓越的承诺，并努力不断改进。实现超出他人和我们自己的期望的期望结果，可用性和价值。

分配的其他职责