OTHER SKILLS & COMPETENCIES

////OTHER SKILLS & COMPETENCIES
OTHER SKILLS & COMPETENCIES2019-02-20T05:37:08+00:00

Data engineering relates to the creation of technology architecture and infrastructure for the financial industry, as well as wider business and organisational application.

Data engineers design, construct, implement, test and maintain technology, thereby creating the infrastructure to make good data available. This in turn informs an organisation’s financial activities, drives profitability and makes it future fit.

They develop, construct, test and maintain architectures, such as databases and large-scale data processing systems. They install continuous pipelines to and from huge pools of filtered information, for others to then pull the relevant data sets for analysis.

These individuals focus and wrestle with problems associated with database integration as well as with messy, unstructured data-sets.

Their ultimate aim is to provide clean, useable data to whomever may require it, while improving a business from the ground up. This includes building on the tech currently in use within the workplace, as well as designing and implementing new technology to propel the organisation forward.

In addition people suited to this career also display the following competencies:

  • Financial market intelligence.
  • Auditing and governance regulations.
  • Financial planning.
  • Risk and compliance.
  • Statistical analysis and modeling.
  • Approach challenges with a clear eye on what is important and employs the right approach / methods to make the maximum use of time and resources.
  • Carefully listens to all stakeholders, including management and end-users, in order to establish their needs.
  • Explore new territories, thinking outside of the box, as well as finding creative and unusual ways to solve problems.
  • Understand the way the industry functions and how data can be collected, analysed and utilised.
  • Maintains flexibility and resilience in the face of BIG DATA developments.
  • Think logically and laterally to solve problems.
  • Understands what drives the industry and how data can contribute to the success of an organization’s strategy.
  • Questions established business practice and brainstorms new approaches to data analysis.
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