Data Engineer

The Opportunity

A great opportunity to join a high-growth, product-led technology business that's investing in its data capabilities as it scales.

You'll join a small, friendly and supportive data function, helping to build and improve the pipelines and datasets that sit behind business reporting and analytics. The team is lean right now, so this role comes with genuine ownership and the chance to shape how data engineering is done going forward.

Working pattern

This is a remote-first role

The Why? (Top 3)

• High ownership, early-stage data function
• You'll be one of the key people helping define standards, patterns, and best practice as the data capability grows.
• BI work with visible business impact
• You'll build pipelines that directly enable reporting and decision-making across the organisation.
• Modern tooling and strong engineering approach
• Hands-on work with AWS and Databricks, focusing on scalable, maintainable data pipelines.

The What...

As a Data Engineer, you'll help build and manage the data platform and tooling that supports reporting and analytics. You'll work cross-functionally with engineers and stakeholders, contribute to technical direction, and help embed robust engineering practices across the data estate.

Core responsibilities include:

• Building and maintaining data pipelines that support BI reporting (AWS QuickSight)
• Developing and optimising SQL-first transformations (this role leans more SQL than Python)
• Working with Databricks / Spark for scalable batch processing (and some streaming exposure where relevant)
• Partnering with stakeholders to deliver reliable, well-structured datasets and reporting outputs
• Contributing to documentation, data quality, version control and deployment best practice
• Supporting the evolution of the data platform as the team grows

What you'll bring

Essential experience:

• Commercial experience in a Data Engineering (or similar) role
• Strong SQL and confidence working in a cloud data environment
• Experience with Databricks and or Spark
• Exposure to AWS
• GitHub and a solid grasp of modern engineering workflows

Nice to have (not required):

• AWS QuickSight
• DBT
• Structured Streaming or real-time pipeline exposure
• Infrastructure as Code (Terraform or CDK)