Principal Data Engineer

at  Aker Systems

Aker Systems was founded in 2017 by a team of experienced technology professionals who recognised an opportunity to provide highly secure enterprise data platforms to large organisations. Aker builds and operates ground-breaking, ultra-secure, high performance, cloud-based data infrastructure for the enterprise. Our proprietary technology solutions drive performance and reduce costs while helping our clients to improve the management and sharing of data across their organisations.
In 2022, Aker Systems was proud to win the ‘Scale up Business of the Year’ award by the British Business Excellence Awards. In 2020 Aker Systems was recognised as a ’One to Watch’ on the Sunday Times Tech Track and was also recognised at the Thames Valley Tech Awards 2020; winning the Thames Valley Tech Company of the year, the Emerging Tech Company and High Growth Tech Business categories.
Most recently in September 2021, we were successfully acquired by a new investor (Abry Partners) who have a deep industry expertise in our field to support us in the next part of our journey and as we continue to grow and diversify as a business.
We encourage people of all different backgrounds and identities to apply. We are committed to maintaining an inclusive, and supportive place for you do your very best work.

As a Principal Data Engineer, you will assist in the development of a secure batch/real-time data platform for a government client leveraging the latest commercial and open-source technologies. This involves getting data from a variety of different sources, getting it into the right format, assuring alignment to target models, and ensuring that data can be made available to downstream consumers.

You will:

• Code, test, and document new or modified data pipelines that meet functional / non- functional business requirements
• Conduct logical and physical database design
• Expand and grows data platform capabilities to solve new data and analytics problems
• Conduct data analysis, identifying feasible solutions and enhancements to dataprocessing challenges
• Ensure that data models are consistent with the data architecture (e.g. entity names,relationships and definitions)
• Perform root cause analysis on internal and external data and processes to answerspecific business questions and identify opportunities for improvement