Data & Analytics Apprentice

at  Cybit

Job Title: Data & Analytics Apprentice
Location: Flexibility to be office based or work from home
Salary: Up to £27,000 depending on skills and experiences.

CYBIT

Our success is people powered, and we’re on a mission to work with the best. Rapid growth, huge opportunities and exciting challenges mean we’re looking for brilliant people to join our team here at Cybit.
Within our Data & Analytics division, we work closely with customers on a diverse range of business intelligence projects to enable them to make the best use of their data to drive critical business decisions. As well as our Data & Analytics division, we also have Managed Service and Cyber Security specialist arms to the business, setting us apart from other IT consultancies.
We operate out of three offices, Berkshire, Newcastle & Belfast, and have 150 employees across Cybit. We have great relationships with our vendors, and we’re a Microsoft Gold Partner, Qlik Select Partner, Alteryx Premier Partner, AWS Advanced Consulting Partner, Palo Alto Platinum Innovator, F5 Gold Partner and more!

DESIRED QUALIFICATIONS:

Education qualifications are not necessary but at least one year of experience withing the field of data, ETL or report creation is desirable.

The Data & Analytics Apprentice will support our internal & client requirements working with technologies such as Qlik, Talend and Microsoft. You’ll assist our clients in a variety of sectors, to allow them to obtain a deeper understanding of their business while helping internal teams generate insights into our operations.

As a quide you will:

• Learn about Data & Analytics through team engagement, our vendors and official learning resources.
• Deliver elements of internal projects to build data assets and visualisations to drive operational improvements.
• Support client projects alongside other team members by applying data engineering techniques around ETL, data warehousing and data quality.
• Produce demonstration platforms for our focus industry solutions.
• Employ advanced data technologies including machine learning techniques to enrich existing data assets.
• Keep up to date with technology advancements with hands-on learning and show & tell engagements with other team members.