Aiimi is seeking an experienced Data Engineer to join our Aiimi Services division for an exciting project, collaborating directly with one of our clients.
We work with a wide range of clients across the UK, offering diverse projects with unique challenges. You should have a strong interest in learning and working with the latest technologies. As a Data Engineer, you will be a self-driven professional with solid experience in data visualization and sourcing/manipulating various data sources as needed.
Requirements
Data analysis and visualisation. The ability to understand the ultimate value and objectives of data analytics solutions is expected, demonstrating keen analytical skills to deliver optimised analyses & visualisations for this requirement. Good experience is required in the use of visualisation software (i.e. Power BI), including the integration of geo-spatial information from our Geographic Information Systems (GIS) to map data.
Data engineering. The ability to source, model and integrate data from multiple sources as part of extract-transform-load (ETL) activities is essential. Individuals must be able to rapidly understand complex data structures/ systems.
Communication & collaboration. Given that the scope here is vague, it is essential that resources are clear, confident communicators, with experience of operating successfully in small, dynamic agile teams. They should be able to support scope development and articulate need/concerns and solutions effectively with both colleagues and business subject matter experts. All resources will be expected to work collaboratively, fully engaging throughout the term of the engagement. Iterative progress will be effectively communicated, approved and managed.
Industry knowledge. Experience of working in a relevant, comparable industry to deliver data engineering and/or analytics solutions. Previous experience with energy/power data in a utility setting would be highly advantageous and welcomed.
Technologies and toolsets. Ideally resources should have proven experience of relevant data and analytics platforms and tooling. These include:
Benefits
