Data Engineer

Our Digital Business Technology team brings together data, analytics, AI and technology capabilities that support our global operations. As our Security business moves to a new Salesforce platform, we're investing in the data infrastructure and integration capabilities needed to connect information across the organisation and unlock its value.

The Opportunity

We're looking for a hands-on Data Engineer to play a key role in a large-scale Salesforce data migration as part of a multi-year Revenue Operations transformation programme.

Over this 12-month fixed-term assignment, you'll help bring together data from a range of enterprise systems, including SAP, transforming and integrating it to create reliable, scalable data pipelines into and out of Salesforce.

You'll be involved in the engineering work from the ground up – building pipelines, developing data models, solving integration challenges and ensuring data is accurate, accessible and fit for purpose.

Working alongside our existing external engineer, and with guidance from Gallagher's Senior Data Engineer and wider Data, Analytics and AI team, you'll be part of a collaborative project with clear deliverables and genuine business impact.

The technology stack includes Azure Data Factory, Databricks, dbt, SQL and Python/PySpark.

It's a great opportunity to put your existing engineering skills to work while gaining deeper exposure to modern data platforms and enterprise-scale migration.

What you’ll be doing

• Building, testing and maintaining cloud-based ELT pipelines and data integration solutions.

• Supporting the migration of data between Salesforce and enterprise platforms including SAP, Genesys Cloud and licensing systems.

• Developing and transforming dimensional data models using SQL, Python and/or PySpark.

• Working across Azure Data Factory, Databricks and dbt environments.

• Improving pipeline performance, scalability, cost efficiency, observability and reliability.

• Applying sound engineering practices across CI/CD, testing, code reviews and technical documentation.

• Collaborating with internal stakeholders, source-system specialists and Slalom engineers to deliver project milestones.

The Fit

You're a practical, technically capable Data Engineer who enjoys solving problems and getting things built. You take ownership of your work, understand the importance of quality and reliability, and can confidently talk through the solutions you've developed and the engineering decisions behind them.

We're interested in what you can do, not just a checklist of technologies.

You don't need to be an architect or have experience across every tool in our stack. Strong engineering fundamentals, hands-on experience and the ability to pick up new technologies will go a long way.

Ideally, you'll bring:

• Commercial experience building and maintaining data pipelines within a cloud environment such as Azure or AWS.

• Strong SQL skills and confidence coding in Python and/or PySpark.

• Experience working with a modern data platform such as Databricks.

• Experience in dimensional data modelling, data quality and pipeline optimisation.

• Familiarity with CI/CD, automated testing, version control and technical documentation.

• Good communication skills and the ability to collaborate across a distributed project team.

Exposure to dbt Core, Azure Data Factory, Salesforce, SAP, APIs or SharePoint integrations would be a bonus.

If you're keen to work on a substantial data transformation, get stuck into modern engineering technologies and build solutions that will have a lasting impact, we'd love to hear from you.

Applications will be reviewed as they are received, and the role may be filled before the closing date.