Data Engineering Manager
Summary
Lead and develop an established data engineering team while owning the technical direction and architecture of a modern cloud data platform built with Python/PySpark, Databricks, Microsoft Fabric and lakehouse/medallion patterns. A hands-on leadership role: reviewing designs, improving CI/CD, testing and data quality, and shaping the long-term platform roadmap with the Head of Data.
I’m recruiting for a Data Engineering Manager to join a large organisation that has made a significant investment in modernising its data capability.
This is a role for someone who sits comfortably between engineering leadership and data platform architecture.
You'll inherit an established Data Engineering team and take responsibility for how they engineer, develop and evolve a modern cloud data platform. You'll manage and develop the team, but this isn't a role for someone who has moved completely away from technology.
They need someone who can challenge an architecture, understand the engineering underneath it and make clear recommendations about how the platform should evolve.
What you'll be responsible for
- Leading and developing a team of Data Engineers
- Owning the technical direction and architecture of the data platform
- Setting engineering standards and ensuring good development practices
- Reviewing designs and challenging technical decisions
- Improving CI/CD, testing, monitoring, data quality and deployment processes
- Building scalable and reliable approaches to data ingestion and transformation
- Working closely with the Head of Data to shape the longer-term platform roadmap
- Communicating technical recommendations clearly to senior and non-technical stakeholders
- Developing a platform capable of supporting future analytics, AI and data products
What we're looking for
You’ll ideally have progressed through a Data Engineering background and moved into technical leadership or management without losing your engineering knowledge.
We're particularly interested in experience across:
- Python / PySpark
- Microsoft Fabric and/or Databricks
- Lakehouse / Medallion architectures
- CI/CD and modern software engineering practices
- Leading and developing Data Engineers
- Working with senior business and technology stakeholders
Microsoft Fabric experience is advantageous rather than essential. Strong Azure/Databricks candidates will absolutely be considered.
The important thing is that you understand good Data Engineering principles and can apply them at platform level – not simply manage delivery.
This could suit an existing Data Engineering Manager, Data Engineering Lead, Data Platform Lead, Principal Data Engineer or hands-on Head of Data Engineering looking for genuine ownership of a modern data environment.