Data Engineer

Join a product team where your pipelines don’t just move data – they become the trusted foundation for reporting, self-service analytics, and AI initiatives across the business.

You’ll sit inside a cross-functional product team with a strong focus on consumption, shaping data so it’s easy for others to find, trust and use.

Responsibilities will include:

• Designing and maintaining dimensional and semantic models optimised for business consumption
• Building reusable transformation logic in dbt that supports multiple downstream use cases
• Orchestrating and maintaining reliable pipelines in Airflow, working in Snowflake as the core platform
• Partnering with BI developers and analysts to make sure datasets are trusted, well-documented, and easy to self-serve
• Maintaining lineage and relationships between analytical assets as the data model evolves
• Contributing to standards and best practice around testing, documentation, and data quality

Skills we are looking for

• Strong data engineering and data pipeline development skills. Experience with Python, dbt and Apache Airflow (essential)
• Experience with Snowflake
• Experience developing transformations using dbt core or Cloud
• Experience working with modern analytics architectures and data product concepts
• Strong understanding of dimensional modelling, Data Vault and other data modelling methodologies
• Experience developing semantic layers and business-facing data structures
• Experience with BI tools such as Power BI
• Understanding of data governance, data quality and metadata management principles
• A self-starter mindset – you spot gaps and drive fixes without hand-holding
• Comfortable working within an Agile product team, collaborating across engineering and business
• Experience working within Agile product teams
• Familiarity with source control, CI/CD and engineering best practices