Data Engineer

Build a greenfield data platform from scratch!

This logistics company is halfway through a massive digital transformation. Legacy monoliths are being dismantled, replaced with a clean, cloud-native, modular stack - and the new data team is central to making it all talk.

You'll be working directly with their Head of Data, building Azure-based pipelines from the ground up, and shaping how the company uses data across 50+ systems. There's real investment, real urgency, and real interest in doing this properly - not endless meetings and PowerPoints.

What you'll be doing:

• Designing, building, and optimising Azure-based data pipelines using Databricks, PySpark, ADF, and Delta Lake

• Implementing a medallion architecture - from raw to curated

• Collaborating with analysts to make data business-ready

• Applying CI/CD and DevOps best practices (Git, Azure DevOps)

• Supporting the team's growth with clean, well-documented code

• Exploring real-time logistics datasets

What they're looking for:

• A strong communicator - someone who can build relationships and help connect silos

• Experience building pipelines in Azure using Databricks, ADF, and PySpark

• Strong SQL and Python skills

• Bonus points if you've worked with Power BI, Azure Purview, or streaming tools

• You're versatile - happy to support analysts and wear multiple hats in a small, growing team

• Genuinely interested in ML/AI (no need to be an expert)

The catch (read this): This is 5 days onsite in their London office. They're building the data team face-to-face, not over Zoom. Candidates must be London/Home Counties-based.

Why now?

• Help build a greenfield platform with a modern Azure stack

• Real business impact - logistics, supply chain, real-time data

• A rare opportunity to shape something properly, from the ground up

Apply here to register your interest!

McGregor Boyall is an equal opportunity employer and do not discriminate on any grounds.