高级分析工程师

You can:

• communicate effectively with technical and non-technical stakeholders
• support and host discussions within a multidisciplinary team, with potentially difficult dynamics
• be an advocate for the team externally
• manage differing stakeholder perspectives

You can:

• undertake data profiling and source system analysis
• present clear insights to colleagues to support the end use of the data

You can:

• experiment with unfamiliar and emerging technologies, or familiar technologies in new data contexts, with guidance
• share what you learn with the team, explaining potential benefits, risks, and practical considerations
• identify opportunities to apply technology to improve data processes or outcomes in an operational setting or the wider organisation

You can:

• build and review complex data models, ensuring adherence to standards
• use data integration tools and languages to integrate and store data, and advise teams on best practice
• ensure data for analysis meets data quality standards and is interoperable with other data sets, enabling reuse
• work with other data professionals to improve modelling and integration patterns and standards

You can:

• design an appropriate metadata repository
• suggest changes to improve current metadata repositories
• understand a range of tools for storing and working with metadata
• advise less experienced members of the team about metadata management

You can:

• initiate and monitor actions to investigate patterns and trends to resolve problems
• effectively consult specialists where required
• determine the appropriate resolution and assist with its implementation
• determine preventative measures

You can:

• lead the design, code, testing and deployment of secure, resilient and maintainable solutions
• continuously improve the codebase and reliability of solutions
• create automation to improve the software development life cycle
• work with others to implement standards and good practice to ensure security, testability and maintainability of solutions

You can:

• review requirements and specifications, and define test conditions
• identify issues and risks associated with work
• analyse and report test activities and results

You can:

• design data architecture that deals with problems spanning different business areas
• identify links between problems to devise common solutions
• work across multiple subject areas, or a single large or complicated subject area
• produce appropriate patterns

您可以：

• 分析一项服务如何融入跨组织的照护路径
• 与临床医生、照护人员和患者合作塑造数字服务
• 解释数字决策对照护、安全和员工工作量的影响

您可以：

• 在工作中应用数据保护原则
• 为数据保护影响评估作出贡献
• 正确处理信息请求和记录

您可以：

• 定义数据质量规则和衡量指标
• 与数据提供方合作，从根本上解决质量问题

您可以：

• 使用临床术语设计数据模型和参考集
• 在术语和分类之间进行映射，并解释映射的局限
• 就产品和分析中的术语使用向团队提供建议

您可以：

• 使用假名化数据，并在发布输出前进行披露检查
• 识别关联数据或详细数据何时可能识别出某位患者