Senior Data Engineer - #2158682

Senior Data Engineer – Python / PySpark / Azure

£70,000–£80,000 + benefits

Location: North West – Hybrid (1 day per week in the office)

Employment: Permanent

I'm recruiting a Senior Data Engineer for an established organisation investing significantly in its data capability.

Over the last couple of years, the business has been modernising a sizeable legacy data estate, moving towards a modern cloud-based environment. With the foundations now in place, the next phase is focused on building scalable data solutions, strengthening engineering practices and making better use of its data.

This is an opportunity for someone who enjoys writing code, solving complex problems and influencing how data engineering is delivered.

The role

You'll join a growing data function, working on the development and improvement of a modern data platform built around Microsoft Azure and Fabric.

The hiring manager is particularly interested in engineers who are genuinely code-led, rather than predominantly working with traditional ETL tools or low-code pipelines.

You'll have the opportunity to take ownership of technical solutions, contribute to architectural decisions and help establish the engineering standards that will underpin the next stage of the platform's development.

Your responsibilities will include:

• Designing, developing and maintaining scalable data pipelines and transformations using Python, PySpark and SQL.
• Building data solutions within modern cloud and lakehouse environments.
• Developing and optimising Spark-based data processing, ideally using Databricks or Fabric notebooks.
• Contributing to data architecture, including lakehouse and Medallion design principles.
• Improving engineering practices around CI/CD, automated testing, version control, monitoring and data quality.
• Working with stakeholders to translate business requirements into reliable, reusable data products.
• Supporting and mentoring other engineers, sharing knowledge and helping establish technical standards.
• Contributing to the ongoing modernisation of the data platform.

What we're looking for

The priority is finding a strong Data Engineer with excellent coding ability and a solid understanding of modern engineering practices.

Ideally, you'll bring:

• Strong commercial Python and SQL experience, particularly developing production data pipelines and transformations.
• Experience with PySpark, Apache Spark or other distributed data-processing technologies.
• Experience working within a Microsoft Azure environment.
• Exposure to Databricks, Microsoft Fabric or comparable modern cloud data platforms.
• An understanding of lakehouse architecture, Delta Lake or Medallion architecture.
• Experience with Git, CI/CD, automated testing and software engineering best practices.
• The ability to take ownership of technical challenges and contribute to solution design.

You don't need to have worked with every technology listed.

Strong Python engineers from other cloud environments will also be considered, particularly those with experience building production-grade pipelines, implementing automated testing and deploying reliable data solutions.

We're more interested in how you engineer than whether you've used every tool in the current technology stack.

Why consider this opportunity?

This isn't a position where you'll simply maintain an established data platform.

There's a substantial amount of engineering work still to deliver, alongside the opportunity to influence technical decisions and help shape how the team operates.

The business is also looking beyond its immediate platform modernisation, with longer-term investment planned around AI, Generative AI and intelligent automation.

For someone who enjoys building things, developing their technical capabilities and working in an environment where good engineering practices are valued, there's plenty of scope to make an impact.

The position offers a salary of up to £80,000, alongside a flexible hybrid arrangement requiring approximately one day per week in the office.