Data Engineer

Introduction

Through our client-facing brands Momentum Group, with Multiply (wellness and rewards programme), and our other specialist brands, including Guardrisk and Eris Property Group, the group enables business and people from all walks of life to achieve their financial goals and life aspirations. We help people grow their savings, protect what matters to them and invest for the future. We help companies and organisations care for and reward their employees and members

Disclaimer

As an applicant, please verify the legitimacy of this job advert on our company career page.

Role Purpose

To leverage data, analytics, statistical modelling, and machine learning techniques to generate actionable business insights, support strategic decision-making, identify risks and opportunities, and drive continuous process improvement. The role is responsible for transforming complex data from multiple sources into meaningful information, predictive models, and visualisations that enhance business performance, improve operational efficiency, support governance requirements, and enable data driven decision-making across the organisation.

Requirements Qualification

• Matric / Grade 12 (Essential)
• Computer sciences Degree relating to coding, data analytics, information systems, data bases etc. ( Essential)
• Honours degree in data Science or related. (Advantageous)

Experience

• 3 - 5 years' working experience as a Data Engineer.
• Databricks experience. (Essential)
• Ability to code in SQL (Essential)
• Machine learning and predictive modelling (Advantageous)
• Experience with different databases (Advantageous)
• Python Experience (Advantageous)

Duties & Responsibilities

• Participate in discovery processes with business stakeholders to identify problems and opportunities that may be addressed with statistical modelling or machine learning.
• Identify, understand, interpret data structures across various databases within the business to facilitate data analysis and continuous monitoring activities.
• Advise on data collection; identify available and relevant data, potentially leveraging third party data sources.
• Contribute to data integrity and cleansing activities in order to increase the quality of data.
• Contribute to the automation and continuous improvement of data and reporting processes.
• Provide and compile data models to proactively identify risks within business, provide insight and to promote reuse and accuracy of reporting.

Competencies

• Examining Information: Analyses and processes information asks probing questions strives to find solutions to problems.
• Interpreting Data: Interprets data rationally by quantifying issues applies technology as a means to evaluating data evaluates information objectively.
• Developing Expertise: Is open to taking up learning opportunities is quick in acquiring knowledge and skills develops expertise by updating specialist knowledge.
• Articulating Information: Is articulate in giving presentations is eloquent and explains things well projects social confidence when articulating information.
• Challenging Ideas: Prepared to disagree and question assumptions challenges ideas and established views comfortable arguing own perspective.
• Team Working: Works participatively with others is democratic and encourages team contributions collaboratively involves others in decision making.
• Managing Tasks:Manages tasks by being organised and methodical plans activities systematically sets priorities for tasks.
• Producing Output: Is focused on activity and works quickly keeps busy and maintains productivity is comfortable multi-tasking to produce output.