Data Engineering is a field in rapid growth thanks to all digital interactions that take place as a natural part of our everyday lives. For Telia Company, data is key for future success. But as the access to data increases, so does the demand of qualified employees with the right skills. Read more in this case study how Telia solved their competence need with tailored reskilling program with AW Academy.
Telia delivers a future-proof analytical platform using modern technology to cover companies' growing need for fast and accessible insights via data. The Analytics team at Telia is a unit with a strong passion for data and has an important role in Telia's journey towards becoming more data driven. Like many other organizations today also Telia is confronted with the IT-skills shortage and struggle with recruiting in the pace needed. Data Engineers and competence within Data Analytics is such an area where the skills need is big.
Having high-quality data available for decisions and advanced algorithms is essential, and we believe that it will only become indispensable in the future. As a telco, we have a lot of data. Turning this data into information is the job of data engineers. They develop code that cleans and transforms data into a usable format and makes it easy for the business to use in their process, says Marius Frøisland, Head of IT Analytics & BI Norway and Denmark – Telia.
A Data Engineer has a good outlook on the job market today and often has a lot of opportunities when looking for a job. Telia Company saw a need of a complementary way of finding new talent in parallel with their traditional recruitment channels. To tackle the competence challenge, Telia Company partnered up with AW Academy and Academic Work to recruit, train and hire people with various backgrounds to their Analytics team.
To meet the needs and demands from Telia, all parties worked together to identify relevant learning outcomes for the program. Via backward design, a tailored curricula were designed and consists of 12 weeks of accelerated learning.
We experience that the AW Group recruitment process and the consecutive training is a good solution for Telia. It gives us access to other profiles and increases our diversity in background, education, and experience. AW Group was also able to gather a larger pool of candidates for each position than we usually are. In addition, through the testing process and preliminary interviews, they reduced the workload on the recruiting managers. Recruitment is usually a time-intensive process for both the recruitment team and the managers, Marius continues.
The Telia Data Engineer program is offered to individuals with different background who have the right cognitive abilities and motivation to undertake a tough accelerated learning program, as the start of their new IT-careers. The participants were chosen in a rigorous recruitment process that consists of tests, interviews, and meetings with hiring manager at Telia. Marius Frøisland lets us know why Telia chose AW Academy and Academic Work as a partner.
We chose AW Group because of the philosophy behind their recruitment and teaching. The program also gives us a lower risk with junior data engineers than a typical recruitment process does. However, the most crucial factor was that it is an excellent way to recruit future employees while giving people a chance to change their careers. The ultimate KPI of success will be how many of the candidates' Telia chose to offer permanent positions and, even more important, how many accept.
After 12 weeks of accelerated learning Telia expands its team with 12 new coworkers in Sweden, Norway, and Denmark. The graduates from Norway and Denmark immediately started working on projects while the Swedish consultants attended extended training tailored to their specific team and local needs. The combination of high level of motivation as well as the often already existing work experience enables productivity and fast introduction to the company.
Via the partnership with AW Academy and Academic Work, Telia secure the talent pipeline within Data Engineering as well as giving motivated individuals the opportunity to reskill into IT in an efficient and qualitative way. It´s a win-win situation!
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