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Data Engineer | £60-65K | London (5 days p/w Onsite)
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.
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Seniority level
* Seniority level
Entry level
Employment type
* Employment type
Full-time
Job function
* Job function
Information Technology
* Industries
Data Infrastructure and Analytics
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