Job Description

Job Advert Summary

The Graduate Intern: Data Analytics will be responsible for managing and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection for cross functional teams.



The Graduate Intern: Data Analytics will also build and automate solutions (dashboards) to provide actionable insights into customer management, operational efficiency and other key business performance metrics.

Minimum Requirements

Education

B Sc in IT (Data Engineering) or similar Postgraduate degree in IT - Data Engineering (preferred)

Knowledge and Skills

:


Knowledge and understanding of relevant database and query solutions, applications and tools. SQL proficiency as well as working familiarity with a visualisation engines (Power BI) Knowledge and understanding of the best practices of the financial services / graduate professional client market Knowledge of information management practices including information lifecycle management, data modelling, master data management and carrying out business audits and requirements gathering. Knowledge and appreciation of the need for consistency in data management and governance

Duties and Responsibilities

Maintain the Analytics Data Warehouse and Data Pipeline environments. Work with teams to automate and audit data flows to ensure clean and available data. Data governance (quality, accessibility, ownership and security). Engaging with stakeholders to obtain an understanding of their data practices to contract, manage and meet expectations. Identifying opportunities to influence the improvement or enhancement of business processes and methodologies by researching and recommending improvement initiatives and effective ways to operate and add value to PPS. Designing and implementing data strategies and systems, through collaboration with the IT and Business teams, to create and maintain the data architecture that will drive various initiatives across the organisation. Work with IT to source and load a wide range of data across our business into the data lake so that it can be used by analysts and developers to develop data solutions for the business Assemble large, complex data sets that meet functional / non-functional business requirements. * Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.