Data Engineer

As a Data Engineer, you’ll be responsible for designing, building and supporting data pipelines and data products across a modern cloud data environment.

You’ll be involved in:

• Building and maintaining ELT/data transformation pipelines using dbt and cloud data platforms
• Developing robust and scalable data pipelines using Python and SQL
• Designing and maintaining data models to support analytics, reporting and data science
• Working with cloud data platforms to optimise performance, data structures and compute costs
• Implementing data quality checks, automated testing and monitoring
• Developing and maintaining CI/CD pipelines and applying software engineering best practice to data development
• Using Git and version control, code reviews and automated deployment processes
• Integrating data from a range of internal and external sources
• Supporting data governance, security and regulatory requirements

We’re looking for an experienced Data Engineer who combines strong technical capability with a genuine software engineering mindset.

You’ll ideally have 5+ years’ commercial experience in data engineering, although we’re open to candidates with strong relevant experience.

We’re particularly interested in candidates with experience across:

• Cloud data warehousing - experience with Snowflake is highly desirable, but not essential. Experience with equivalent platforms such as Databricks, Azure Synapse, BigQuery or Redshift will also be considered.
• dbt - experience building data models, tests, incremental models and transformations would be advantageous.
• Python - data engineering, automation, ingestion and pipeline development
• SQL - including query optimisation and performance tuning
• Git and CI/CD - with experience working in a modern software engineering environment
• Data warehousing and data modelling principles
• Building and supporting production-grade data pipelines

Snowflake experience would be a strong advantage, but it is not a prerequisite. If you have strong experience with another modern cloud data platform and the right engineering background, we’d still be keen to hear from you.

Experience of Microsoft Azure would also be highly advantageous, particularly:

• Azure Data Factory
• Azure SQL
• Azure Data Lake/ADLS
• Azure DevOps
• Microsoft Fabric
• Azure Databricks

Experience with PySpark, Airflow, Dagster, Prefect or other orchestration technologies would also be useful.

We’re particularly interested in people who have worked with modern data platforms and understand the principles of ELT, automation, testing, observability, data quality and infrastructure-as-code.

What You’ll Bring

• A strong understanding of modern data engineering practices
• A genuine interest in building well-engineered, maintainable data solutions
• Strong problem-solving and analytical skills
• The ability to work independently and take ownership
• Good communication skills, with the ability to explain technical concepts to non-technical stakeholders
• A collaborative approach and experience working in Agile environments
• Curiosity and a desire to influence and improve the way data engineering is done

You’ll have the chance to:

• Help shape a modern Snowflake and dbt data platform
• Influence engineering standards, architecture and ways of working
• Work with modern cloud and data technologies
• Build data products that have a direct impact on business decision-making