Data Platform Manager

🚀 Data Platform Manager – Newcastle | Hybrid

I’m working with a large, established organisation in Newcastle that is investing significantly in its Data, AI and R&D capability and is looking for a Data Platform Manager to take technical ownership of its evolving data platform.

Despite the title, this isn’t a traditional people-management position.

They need someone who can take ownership of the platform itself – providing technical direction, establishing how it should be structured and operated, and ensuring the right engineering, DevOps and delivery practices are in place as its use continues to grow.

The environment includes:

🔹 Microsoft Fabric & Databricks

🔹 Azure DevOps / CI/CD

🔹 Power BI & semantic models

🔹 Lakehouse architecture / Delta Lake

🔹 Data pipelines, ingestion & orchestration

🔹 Data Science, AI & GenAI use cases

You’ll work closely with Data Engineering, QA, Data Science and R&D, helping take ideas and models from experimentation through to secure, scalable production solutions.

There’s a really interesting roadmap ahead.

Current and future use cases range from delivering Power BI reporting and profitability models through to client intelligence, resource applications and the use of AI agents.

The challenge is making sure the underlying platform can support all of that.

That means thinking beyond an individual pipeline or application and considering the wider picture: architecture, capacity, scalability, security, infrastructure, access controls, performance, cost and operational support.

We’re therefore looking for someone technically strong who understands areas such as:

• Modern data platform architecture

• Microsoft Fabric and/or Databricks

• Data pipelines, ingestion and orchestration

• Azure DevOps and CI/CD

• Data modelling and Lakehouse patterns

• Platform performance, scalability and capacity

• Security, RBAC and enterprise controls

• Productionising Data Science / ML / AI solutions

• Agile/Scrum delivery and good engineering processes

You don't necessarily need to be the deepest specialist in every technology.

What’s more important is having enough technical breadth to look across the platform, understand how the pieces fit together, identify what needs to change and provide clear technical direction.

This could suit an experienced Data Platform Engineer, Lead Data Engineer, Data Platform Lead or Data Architect who wants broader ownership without moving away from the technology.