Senior Data Engineer

Role: Data Engineer

Location: Remote

Head office: Ireland

Salary: €65,000 - €80,000 basic + bonus

Our organization has partnered exclusively with a global consumer brand that manufactures a world-leading product across six countries and has recently entered the US market. They are PE-backed and entering a critical growth phase, with a clear ambition to double revenue from ~€200m to €400m. They have recently brought in a new CIO and Head of Data to reset the technology function.

The focus is clear:

• Bring capability back in-house
• Reduce reliance on third parties
• Improve control, visibility, and governance
• Introduce proper delivery discipline across the data estate

The environment works today. But it’s at an inflection point now’s the time to mature it properly, with strong backing from the executive leadership team.

The role

This is a hands-on Data Engineering role first and foremost. You’ll be coming into a live environment that needs stabilizing and improving, not a blank canvas. The job isn’t to rip everything out and start again. It’s to simplify, structure, and strengthen what’s already there, then help shape what comes next.

What you’ll be doing

• Building and improving data pipelines across SQL Server and Azure Data Factory
• Bringing stronger engineering discipline (documentation, testing, change control, reuse)
• Supporting a more structured and controlled delivery approach
• Working closely with the Head of Data on governance and standards
• Contributing to platform simplification and cleaner design over time
• Engaging in architecture and design conversations (without needing to be “the architect”)

Tech environment

• SQL Server
• T-SQL (stored procedures, views, functions)
• Azure Data Factory
• Power BI downstream
• SAP as a core data source
• A mix of internal and external data feeds

What they’re looking for

• Strong SQL Server / T-SQL capability
• Solid experience with Azure Data Factory and pipeline engineering
• Comfortable working in environments being improved, not built from scratch
• Strong engineering habits—structure, documentation, testing, control

Python is useful, but not the driver. Bonus if you’ve worked with:

• SAP or ERP-led environments
• Supply chain / FMCG / retail data
• Broader Microsoft data stack

What success looks like

• A more stable, controlled data platform
• Clear standards and governance in place
• Cleaner, more reliable pipelines
• Improved data quality across the business
• Reduced reliance on spreadsheets and workarounds
• Foundations in place for future scale

The kind of person who fits

• Pragmatic and grounded
• Low ego, high ownership
• Comfortable working across both technical and business teams
• Able to bring structure without overengineering
• Someone who actually cares about doing things properly

If you want greenfield, this isn’t it. If you want to take a business at scale, bring structure to how data is done, and play a key role in getting it ready for the next phase, this is where it gets interesting.