Hands on Azure Data Engineering Manager

UK Remote - Nottingham office.

Salary is ranging from £60,000 to £75,000 depending on experience.

2 stage interview process before 2025.

My client is committed to providing more efficient, sustainable heating solutions for customers and property owners. With a mission that values people and the planet alongside profit, they play a pivotal role in supporting the UK's journey towards net zero. Managing heat networks is complex, but their vast data sets offer the potential to transform the industry, making this a particularly exciting time to join their expanding team, with excellent opportunities for long-term career development.

This is a fantastic opportunity for an experienced Data Engineer to leverage their skills in building out the data team's capabilities, while mentoring existing team members to reach new heights of excellence.

The role requires someone confident in mentoring others, with strong communication skills to engage effectively with external stakeholders. The ideal candidate will have the following skill set:

• 4+ years of experience in Azure Data Engineering.
• 2+ years in a management position, covering: team management, staff development, and setting clear performance goals.
• Hands on experience in leading data engineering efforts, particularly in the design and maintenance of scalable data pipelines, data lakes, or lakehouse architectures.

Proficiency in Python and data visualisation tools such as Power BI or Tableau, along with a strong understanding of software design patterns, cloud deployment, and principles such as SOLID and CRUD, would be advantageous but is not essential.

Benefits includethe option to work abroad for up to two weeks per year, discretionary bonuses, and supported career progression. If this sounds like the right next step in your career, please apply now.

Desired Skills and Experience

4+ years of experience in Azure Data Engineering.

2+ years in a management position, covering: team management, staff development, and setting clear performance goals.

Hands on experience in leading data engineering efforts, particularly in the design and maintenance of scalable data pipelines, data lakes, or lakehouse architectures.