Graduate Intern: Data Analytics

Job Advert Summary

To support the collection, management, and analysis of business data to enable informed decision-making across the organisation. The role will assist in maintaining data pipelines, improving data quality and accessibility, and developing automated reporting solutions and dashboards that provide actionable insights into customer trends, operational performance, and key business metrics.### Minimum Requirements

Education

• BSc 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.