Job Description

Job description

What you’ll be doing
  • Build and maintain production-grade data pipelines using SQL, Python and dbt
  • Design and optimise analytics-ready data models in Snowflake or BigQuery
  • Own dbt projects end-to-end: models, tests, documentation and deployments
  • Implement and maintain CI/CD pipelines for data workflows (Git-based version control, automated testing, promotion between environments)
  • Work closely with analysts and downstream users to turn raw data into reliable, well-modelled datasets
  • Monitor pipeline performance, data freshness and failures; fix issues before users feel them
  • Improve data quality through testing, observability and better modelling patterns
  • Contribute to platform standards and engineering best practices
    • Tech stack
  • SQL (advanced)
  • Python
  • dbt (essential)
  • Snowflake or BigQuery
  • Git + CI/CD (e.g. GitHub Actions, GitLab CI, Azure DevOps)
  • Cloud data platforms (AWS / GCP / Azure)
    • What we’re looking for
  • Deep SQL capability and real-world Python usage (not just scripts)
  • Proven experience delivering production dbt projects
  • Experience working with large datasets in Snowflake or BigQuery
  • Understanding of CI/CD concepts applied to data (testing, versioning, deployment)
  • Comfortable working in a collaborative, engineering-led environment
  • Pragmatic mindset: you care about reliability, performance and maintainability
    • Nice to have
  • Orchestration tools (Airflow, Prefect, Dagster)
  • Data quality / observability tooling
  • Experience in enterprise-scale data platforms
  • Exposure to security, access controls and governance in cloud data environments

    • Why Join?
  • Work on a modern, cloud-based data platform
  • Influence how data is used across market leader
  • Flexible working and strong focus on wellbeing
  • Long-term career growth in a stable, purpose-driven business

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