Lead Data Engineer

Own the technical direction of a data engagement, setting standards for pipeline architecture, data modelling, testing, and operational readiness

Lead and technically direct a team of data engineers, allocating work, reviewing designs and code, and unblocking technical challenges

Design and evolve data platform architecture on Microsoft Fabric, including data pipelines, Azure OneLake, and the broader Azure ecosystem

Set and enforce CI/CD, testing, and operational practices across the engagement's data engineering workflows, using Azure DevOps

Build professional relationships with key client stakeholders, translating business and data requirements into a coherent technical roadmap

Troubleshoot and resolve the most complex issues in live data pipelines, and lead incident response when things go wrong

We'd love to talk to you if you:

Have extensive hands-on experience with a modern cloud data platform such as Microsoft Fabric (our current client's platform), Databricks, Snowflake, or Synapse, including designing production data platforms — the platform is the wrapper, not the skill, and strong engineering depth on one transfers readily to another

Have deep SQL expertise and a strong grasp of data modelling and architecture (Kimball, data vault, medallion/lakehouse patterns, or domain modelling) — this is the clearest line between someone who operates a platform and someone who can design on top of it, and it's provider-agnostic

Have strong proficiency in Python and PySpark for batch/ELT data processing at scale (this role centres on batch pipeline engineering — we treat streaming/real-time as a separate discipline and never assume the two are interchangeable)

Have led or technically directed a team of data engineers, setting standards for pipeline design, testing, and delivery

Have experience owning CI/CD and operational practices for data engineering workflows, ideally using Azure DevOps

Are experienced working directly with client stakeholders, building trust and challenging where appropriate

Have familiarity with the broader Azure ecosystem, including Azure OneLake and Azure ML, particularly for model industrialisation

What we’ll offer you:

We trust people to do their best work. That means flexibility over rigid rules, impact over activity, and real investment in your growth both professionally and personally. You’ll be part of a supportive, and friendly culture, surrounded by smart, curious people who care deeply about what they do. We offer flexible working, including hybrid and remote options. Our office hubs are located in Edinburgh, Leeds, Manchester, London and Bulgaria, with occasional travel to client sites or CreateFuture offices when needed.

We trust you to manage your time balancing collaboration with client time and focused work. What matters is the impact you have, not how busy you look.

Our hiring process

We try to keep our hiring process clear, fair and respectful of your time. We aim to get back to everyone who applies and we will be upfront about where you are in the process.

It usually looks like this:

Call with our Talent Acquisition Team 

Role specific capability interview 

Depending on the role, we might also ask you to do a short presentation, a practical or technical task or have a values focused conversation. We will explain what is involved before anything happens.

Inclusion at CreateFuture 

We believe diverse teams build better workplaces and better products. We want CreateFuture to be a place where people feel able to be themselves and do their best work.

If you need any adjustments or support during the application process, just. We will do what we can to help.

We look forward to your application!

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