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Data Engineer

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Hybrid

Data Engineer

Change Digital – Digital & Tech Recruitment

Data Engineer

Skills

SQL QueriesData EngineeringPythonSnowflakeGitdbtPySparkApache AirflowAzure

2 months ago

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Important information


Contract type:

Permanent

Location:

Glasgow City, Glasgow, UK

Work mode:

Hybrid

Published on:

14 August 2026

What they need


Data Engineer | Snowflake | dbt | Python

Are you a Data Engineer who wants to do more than maintain legacy systems?

My client is investing in a modern, cloud-agnostic data platform centred around Snowflake and dbt, and are looking for a talented Data Engineer to help shape its future. This is an exciting opportunity to join their Data Team at a pivotal stage of their transformation journey.

Working alongside analysts, data scientists and business stakeholders, you'll design, build and optimise scalable data solutions that drive trusted insights across the organisation. This is a role for someone who enjoys solving complex challenges, influencing technical direction and applying software engineering best practices to data.

Its hybrid working, typically 2 days a week in their Glasgow city centre office but can be flexible.

What You'll Be Doing

  • Building and maintaining scalable ELT pipelines using dbt and Snowflake
  • Developing robust, tested and documented data models
  • Optimising SQL, data transformations and warehouse performance
  • Implementing data quality, testing and observability practices
  • Applying CI/CD, version control and engineering discipline to data development
  • Working closely with stakeholders to deliver impactful data products
  • Contributing to architecture decisions and the evolution of our data platform

What We're Looking For

Essential

  • 5+ years' experience in Data Engineering
  • Strong SQL skills, including optimisation and performance tuning
  • Hands-on experience with dbt (Core or Cloud)
  • Experience with Snowflake or other modern cloud data warehouse technologies
  • Python development experience for data engineering and automation
  • Experience with Git, CI/CD and modern software engineering practices
  • Azure Data Factory, Azure SQL or Microsoft Fabric
  • Strong understanding of data warehousing and data modelling concepts

Nice to Have

  • Airflow, Dagster, Prefect or similar orchestration tools
  • PySpark or distributed data processing experience
  • Exposure to data governance, lineage or catalogue solutions

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